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\n  \n 2023\n \n \n (18)\n \n \n
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\n \n\n \n \n \n \n \n FourierNet: Shape-Preserving Network for Henle's Fiber Layer Segmentation in Optical Coherence Tomography Images.\n \n \n \n\n\n \n Cansiz, S.; Kesim, C.; Bektas, S. N.; Kulali, Z.; Hasanreisoglu, M.; and Gunduz-Demir, C.\n\n\n \n\n\n\n IEEE Journal of Biomedical and Health Informatics, 27(2): 1036-1047. 2023.\n \n\n\n\n
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@article{9973287,\n    author = {Cansiz, Selahattin and Kesim, Cem and Bektas, Sevval Nur and Kulali, Zeynep and Hasanreisoglu, Murat and Gunduz-Demir, Cigdem},\n    journal = {IEEE Journal of Biomedical and Health Informatics},\n    title = {FourierNet: Shape-Preserving Network for Henle's Fiber Layer Segmentation in Optical Coherence Tomography Images},\n    year = {2023},\n    volume = {27},\n    number = {2},\n    pages = {1036-1047},\n    doi = {10.1109/JBHI.2022.3225425}}
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\n \n\n \n \n \n \n \n Precise Event Sampling on AMD Versus Intel: Quantitative and Qualitative Comparison.\n \n \n \n\n\n \n Sasongko, M. A.; Chabbi, M.; Kelly, P. H J; and Unat, D.\n\n\n \n\n\n\n IEEE Transactions on Parallel and Distributed Systems, 34(5): 1594-1608. 2023.\n \n\n\n\n
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@article{10068807,\n    author = {Sasongko, Muhammad Aditya and Chabbi, Milind and Kelly, Paul H J and Unat, Didem},\n    journal = {IEEE Transactions on Parallel and Distributed Systems},\n    title = {Precise Event Sampling on AMD Versus Intel: Quantitative and Qualitative Comparison},\n    year = {2023},\n    volume = {34},\n    number = {5},\n    pages = {1594-1608},\n    doi = {10.1109/TPDS.2023.3257105}}
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\n \n\n \n \n \n \n \n \n AffectON: Incorporating Affect Into Dialog Generation.\n \n \n \n \n\n\n \n Buçinca, Z.; Yemez, Y.; Erzin, E.; and Sezgin, M.\n\n\n \n\n\n\n IEEE Trans. Affect. Comput., 14(1): 823–835. jan 2023.\n \n\n\n\n
\n\n\n\n \n \n \"AffectON:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{10.1109/TAFFC.2020.3043067,\n    author = {Bu\\c{c}inca, Zana and Yemez, Y\\"{u}cel and Erzin, Engin and Sezgin, Metin},\n    title = {AffectON: Incorporating Affect Into Dialog Generation},\n    year = {2023},\n    issue_date = {Jan.-March 2023},\n    publisher = {IEEE Computer Society Press},\n    address = {Washington, DC, USA},\n    volume = {14},\n    number = {1},\n    issn = {1949-3045},\n    url = {https://doi.org/10.1109/TAFFC.2020.3043067},\n    doi = {10.1109/TAFFC.2020.3043067},\n    abstract = {Due to its expressivity, natural language is paramount for explicit and implicit affective state communication among humans. The same linguistic inquiry (e.g., <italic>How are you?</italic>) might induce responses with different affects depending on the affective state of the conversational partner(s) and the context of the conversation. Yet, most dialog systems do not consider affect as constitutive aspect of response generation. In this article, we introduce <italic>AffectON</italic>, an approach for generating affective responses during inference. For generating language in a targeted affect, our approach leverages a probabilistic language model and an affective space. <italic>AffectON</italic> is language model agnostic, since it can work with probabilities generated by any language model (e.g., sequence-to-sequence models, neural language models, n-grams). Hence, it can be employed for both affective dialog and affective language generation. We experimented with affective dialog generation and evaluated the generated text objectively and subjectively. For the subjective part of the evaluation, we designed a custom user interface for rating and provided recommendations for the design of such interfaces. The results, both subjective and objective demonstrate that our approach is successful in pulling the generated language toward the targeted affect, with little sacrifice in syntactic coherence.},\n    journal = {IEEE Trans. Affect. Comput.},\n    month = {jan},\n    pages = {823–835},\n    numpages = {13},\n}\n\n
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\n Due to its expressivity, natural language is paramount for explicit and implicit affective state communication among humans. The same linguistic inquiry (e.g., How are you?) might induce responses with different affects depending on the affective state of the conversational partner(s) and the context of the conversation. Yet, most dialog systems do not consider affect as constitutive aspect of response generation. In this article, we introduce AffectON, an approach for generating affective responses during inference. For generating language in a targeted affect, our approach leverages a probabilistic language model and an affective space. AffectON is language model agnostic, since it can work with probabilities generated by any language model (e.g., sequence-to-sequence models, neural language models, n-grams). Hence, it can be employed for both affective dialog and affective language generation. We experimented with affective dialog generation and evaluated the generated text objectively and subjectively. For the subjective part of the evaluation, we designed a custom user interface for rating and provided recommendations for the design of such interfaces. The results, both subjective and objective demonstrate that our approach is successful in pulling the generated language toward the targeted affect, with little sacrifice in syntactic coherence.\n
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\n \n\n \n \n \n \n \n The eHRI database: a multimodal database of engagement in human–robot interactions.\n \n \n \n\n\n \n Kesim, E.; Numanoglu, T.; Bayramoglu, O.; Turker, B. B.; Hussain, N.; Sezgin, M.; Yemez, Y.; and Erzin, E.\n\n\n \n\n\n\n Language Resources and Evaluation,1–25. 2023.\n \n\n\n\n
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@article{kesim2023ehri,\n    title = {The eHRI database: a multimodal database of engagement in human--robot interactions},\n    author = {Kesim, Ege and Numanoglu, Tugce and Bayramoglu, Oyku and Turker, Bekir Berker and Hussain, Nusrah and Sezgin, Metin and Yemez, Yucel and Erzin, Engin},\n    journal = {Language Resources and Evaluation},\n    pages = {1--25},\n    year = {2023},\n    publisher = {Springer},\n}\n\n
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\n \n\n \n \n \n \n \n ST360IQ: No-Reference Omnidirectional Image Quality Assessment with Spherical Vision Transformers.\n \n \n \n\n\n \n Jabbari Tofighi, N.; Hedi Elfkir, M.; Imamoglu, N.; Ozcinar, C.; Erdem, E.; and Erdem, A.\n\n\n \n\n\n\n arXiv e-prints,arXiv–2303. 2023.\n \n\n\n\n
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@article{jabbari2023st360iq,\n    title = {ST360IQ: No-Reference Omnidirectional Image Quality Assessment with Spherical Vision Transformers},\n    author = {Jabbari Tofighi, Nafiseh and Hedi Elfkir, Mohamed and Imamoglu, Nevrez and Ozcinar, Cagri and Erdem, Erkut and Erdem, Aykut},\n    journal = {arXiv e-prints},\n    pages = {arXiv--2303},\n    year = {2023},\n}\n\n
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\n \n\n \n \n \n \n \n A Bayesian Perspective for Determinant Minimization Based Robust Structured Matrix Factorization.\n \n \n \n\n\n \n Tatli, G.; and Erdogan, A. T\n\n\n \n\n\n\n In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 1–5, 2023. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{tatli2023bayesian,\n    title = {A Bayesian Perspective for Determinant Minimization Based Robust Structured Matrix Factorization},\n    author = {Tatli, Gokcan and Erdogan, Alper T},\n    booktitle = {ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    pages = {1--5},\n    year = {2023},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n An overview of affective speech synthesis and conversion in the deep learning era.\n \n \n \n\n\n \n Triantafyllopoulos, A.; Schuller, B. W; İymen, G.; Sezgin, M.; He, X.; Yang, Z.; Tzirakis, P.; Liu, S.; Mertes, S.; André, E.; and others\n\n\n \n\n\n\n Proceedings of the IEEE. 2023.\n \n\n\n\n
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@article{triantafyllopoulos2023overview,\n    title = {An overview of affective speech synthesis and conversion in the deep learning era},\n    author = {Triantafyllopoulos, Andreas and Schuller, Bj{\\"o}rn W and {\\.I}ymen, G{\\"o}k{\\c{c}}e and Sezgin, Metin and He, Xiangheng and Yang, Zijiang and Tzirakis, Panagiotis and Liu, Shuo and Mertes, Silvan and Andr{\\'e}, Elisabeth and others},\n    journal = {Proceedings of the IEEE},\n    year = {2023},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Decentralized Healthcare Systems with Federated Learning and Blockchain.\n \n \n \n\n\n \n Zekiye, A.; and Ozkasap, O.\n\n\n \n\n\n\n In Proceedings of 14th Turkish Congress of Medical Informatics, volume 16, pages 18, 2023. \n \n\n\n\n
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@inproceedings{zekiye2023decentralized,\n    title = {Decentralized Healthcare Systems with Federated Learning and Blockchain},\n    author = {Zekiye, Abdulrezzak and Ozkasap, Oznur},\n    booktitle = {Proceedings of 14th Turkish Congress of Medical Informatics},\n    volume = {16},\n    number = {18},\n    pages = {18},\n    year = {2023},\n}\n\n
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\n \n\n \n \n \n \n \n Lessons Learned from a Citizen Science Project for Natural Language Processing.\n \n \n \n\n\n \n Klie, J.; Lee, J.; Stowe, K.; Şahin, G. G.; Moosavi, N. S.; Bates, L.; Petrak, D.; De Castilho, R. E.; and Gurevych, I.\n\n\n \n\n\n\n arXiv preprint arXiv:2304.12836. 2023.\n \n\n\n\n
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@article{klie2023lessons,\n    title = {Lessons Learned from a Citizen Science Project for Natural Language Processing},\n    author = {Klie, Jan-Christoph and Lee, Ji-Ung and Stowe, Kevin and {\\c{S}}ahin, G{\\"o}zde G{\\"u}l and Moosavi, Nafise Sadat and Bates, Luke and Petrak, Dominic and De Castilho, Richard Eckart and Gurevych, Iryna},\n    journal = {arXiv preprint arXiv:2304.12836},\n    year = {2023},\n}\n\n
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\n \n\n \n \n \n \n \n Online Interpretation of Sketched Drawings.\n \n \n \n\n\n \n Sezgin, T M.\n\n\n \n\n\n\n In Interactive Sketch-based Interfaces and Modelling for Design, pages 57–77. River Publishers, 2023.\n \n\n\n\n
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@incollection{sezgin2023online,\n    title = {Online Interpretation of Sketched Drawings},\n    author = {Sezgin, T Metin},\n    booktitle = {Interactive Sketch-based Interfaces and Modelling for Design},\n    pages = {57--77},\n    year = {2023},\n    publisher = {River Publishers},\n}\n\n
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\n \n\n \n \n \n \n \n Precise Event Sampling on AMD Versus Intel: Quantitative and Qualitative Comparison.\n \n \n \n\n\n \n Sasongko, M. A.; Chabbi, M.; Kelly, P. H.; and Unat, D.\n\n\n \n\n\n\n IEEE Transactions on Parallel and Distributed Systems, 34(5): 1594–1608. 2023.\n \n\n\n\n
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@article{sasongko2023precise,\n    title = {Precise Event Sampling on AMD Versus Intel: Quantitative and Qualitative Comparison},\n    author = {Sasongko, Muhammad Aditya and Chabbi, Milind and Kelly, Paul HJ and Unat, Didem},\n    journal = {IEEE Transactions on Parallel and Distributed Systems},\n    volume = {34},\n    number = {5},\n    pages = {1594--1608},\n    year = {2023},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Resolving Conflicts During Human-Robot Co-Manipulation.\n \n \n \n\n\n \n Al-Saadi, Z.; Hamad, Y.; Aydin, Y.; Kucukyilmaz, A.; and Basdogan, C.\n\n\n \n\n\n\n In ACM/IEEE International Conference on Human-Robot Interaction, Stockholm, 2023., 01 2023. \n \n\n\n\n
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@inproceedings{inproceedings,\n    author = {Al-Saadi, Zaid and Hamad, Yahya and Aydin, Yusuf and Kucukyilmaz, Ayse and Basdogan, Cagatay},\n    year = {2023},\n    month = {01},\n    title = {Resolving Conflicts During Human-Robot Co-Manipulation},\n    booktitle = {ACM/IEEE International Conference on Human-Robot Interaction, Stockholm, 2023.},\n}\n\n
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\n \n\n \n \n \n \n \n Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring.\n \n \n \n\n\n \n Luchini, C.; Pantanowitz, L.; Adsay, V.; Asa, S.; Antonini, P.; Girolami, I.; Veronese, N.; Nottegar, A.; Cingarlini, S.; Landoni, L.; Brosens, L.; Verschuur, A.; Mattiolo, P.; Pea, A.; Mafficini, A.; Milella, M.; Niazi, M. K. K.; Gurcan, M.; Eccher, A.; and Scarpa, A.\n\n\n \n\n\n\n Modern Pathology, 35. 03 2023.\n \n\n\n\n
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@article{adsay2023simplified,\n    author = {Luchini, Claudio and Pantanowitz, Liron and Adsay, Volkan and Asa, Sylvia and Antonini, Pietro and Girolami, Ilaria and Veronese, Nicola and Nottegar, Alessia and Cingarlini, Sara and Landoni, Luca and Brosens, Lodewijk and Verschuur, Anna and Mattiolo, Paola and Pea, Antonio and Mafficini, Andrea and Milella, Michele and Niazi, Muhammad Khalid Khan and Gurcan, Metin and Eccher, Albino and Scarpa, Aldo},\n    year = {2023},\n    month = {03},\n    title = {Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring},\n    volume = {35},\n    journal = {Modern Pathology},\n    doi = {10.1038/s41379-022-01055-1},\n}\n\n
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\n \n\n \n \n \n \n \n Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation.\n \n \n \n\n\n \n Bozkurt, B.; Isfendiyaroglu, A.; Pehlevan, C.; and Erdogan, A. T\n\n\n \n\n\n\n arXiv preprint arXiv:2210.04222. 2023.\n \n\n\n\n
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@article{bozkurt2023correlative,\n    title = {Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation},\n    author = {Bozkurt, Bariscan and Isfendiyaroglu, Ates and Pehlevan, Cengiz and Erdogan, Alper T},\n    journal = {arXiv preprint arXiv:2210.04222},\n    year = {2023},\n}\n\n
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\n \n\n \n \n \n \n \n DiabML: AI-assisted diabetes diagnosis method with meta-heuristic-based feature selection.\n \n \n \n\n\n \n Hayyolalam, V.; and Ozkasap, O.\n\n\n \n\n\n\n In Proceedings of 14th Turkish Congress of Medical Informatics, 2023., 03 2023. \n \n\n\n\n
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@inproceedings{hayyolalam2023assisted,\n    author = {Hayyolalam, Vahideh and Ozkasap, Oznur},\n    year = {2023},\n    month = {03},\n    title = {DiabML: AI-assisted diabetes diagnosis method with meta-heuristic-based feature selection},\n    booktitle = {Proceedings of 14th Turkish Congress of Medical Informatics, 2023.},\n}\n\n
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\n \n\n \n \n \n \n \n Metaqa: Combining expert agents for multi-skill question answering.\n \n \n \n\n\n \n Puerto, H.; Şahin, G. G.; and Gurevych, I.\n\n\n \n\n\n\n arXiv preprint arXiv:2112.01922. 2023.\n \n\n\n\n
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@article{puerto2023metaqa,\n    title = {Metaqa: Combining expert agents for multi-skill question answering},\n    author = {Puerto, Haritz and {\\c{S}}ahin, G{\\"o}zde G{\\"u}l and Gurevych, Iryna},\n    journal = {arXiv preprint arXiv:2112.01922},\n    year = {2023},\n}\n\n
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\n \n\n \n \n \n \n \n Learning Markerless Robot-Depth Camera Calibration and End-Effector Pose Estimation.\n \n \n \n\n\n \n Sefercik, B. C.; and Akgun, B.\n\n\n \n\n\n\n In Conference on Robot Learning, pages 1586–1595, 2023. PMLR\n \n\n\n\n
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@inproceedings{sefercik2023learning,\n    title = {Learning Markerless Robot-Depth Camera Calibration and End-Effector Pose Estimation},\n    author = {Sefercik, Bugra Can and Akgun, Baris},\n    booktitle = {Conference on Robot Learning},\n    pages = {1586--1595},\n    year = {2023},\n    organization = {PMLR},\n}\n\n
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\n \n\n \n \n \n \n \n The internet of energy systems: Blockchain and smart contracts meet federated learning.\n \n \n \n\n\n \n A. Zekiye, O. O.\n\n\n \n\n\n\n 2023.\n \n\n\n\n
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@conference{zekiye2023ioe,\n    author = {A. Zekiye, O. Ozkasap},\n    title = {The internet of energy systems: Blockchain and smart contracts meet federated learning},\n    booktitle = {IEEE International Conference on Blockchain and Cryptocurrency (ICBC),},\n    year = {2023},\n}\n\n
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\n \n\n \n \n \n \n \n An Information Maximization Based Blind Source Separation Approach for Dependent and Independent Sources.\n \n \n \n\n\n \n Erdogan, A. T.\n\n\n \n\n\n\n In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 4378-4382, 2022. \n \n\n\n\n
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@inproceedings{9746099,\n    author = {Erdogan, Alper T.},\n    booktitle = {ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    title = {An Information Maximization Based Blind Source Separation Approach for Dependent and Independent Sources},\n    year = {2022},\n    pages = {4378-4382},\n    doi = {10.1109/ICASSP43922.2022.9746099}}
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\n \n\n \n \n \n \n \n Training Socially Engaging Robots: Modeling Backchannel Behaviors with Batch Reinforcement Learning.\n \n \n \n\n\n \n Hussain, N.; Erzin, E.; Sezgin, T. M.; and Yemez, Y.\n\n\n \n\n\n\n IEEE Transactions on Affective Computing, 13(4): 1840-1853. 2022.\n \n\n\n\n
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@article{9829283,\n    author = {Hussain, Nusrah and Erzin, Engin and Sezgin, T. Metin and Yemez, Y{\\"u}cel},\n    journal = {IEEE Transactions on Affective Computing},\n    title = {Training Socially Engaging Robots: Modeling Backchannel Behaviors with Batch Reinforcement Learning},\n    year = {2022},\n    volume = {13},\n    number = {4},\n    pages = {1840-1853},\n    doi = {10.1109/TAFFC.2022.3190233}}
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\n \n\n \n \n \n \n \n \n Affective Burst Detection from Speech using Kernel-fusion Dilated Convolutional Neural Networks.\n \n \n \n \n\n\n \n Köprü, B.; and Erzin, E.\n\n\n \n\n\n\n In 2022 30th European Signal Processing Conference (EUSIPCO), pages 105-109, 2022. IEEE\n \n\n\n\n
\n\n\n\n \n \n \"AffectivePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@inproceedings{9909582,\n    author = {K{\\"{o}}pr{\\"{u}}, Berkay and Erzin, Engin},\n    booktitle = {2022 30th European Signal Processing Conference (EUSIPCO)},\n    title = {Affective Burst Detection from Speech using Kernel-fusion Dilated Convolutional Neural Networks},\n    year = {2022},\n    pages = {105-109},\n    url = {https://ieeexplore.ieee.org/document/9909582},\n    abstract = {As speech interfaces are getting richer and widespread, speech emotion recognition promises more attractive applications. In the continuous emotion recognition (CER) problem, tracking changes across affective states is an essential and desired capability. Although CER studies widely use correlation metrics in evaluations, these metrics do not always capture all the high-intensity changes in the affective domain. In this paper, we define a novel affective burst detection problem to capture high-intensity changes of the affective attributes accurately. We formulate a two-class classification approach to isolate affective burst regions over the affective state contour for this problem. The proposed classifier is a kernel-fusion dilated convolutional neural network (KFDCNN) architecture driven by speech spectral features to segment the affective attribute contour into idle and burst sections. Experimental evaluations are performed on the RECOLA and CreativeIT datasets. The proposed KFDCNN outperforms baseline feedforward neural networks on both datasets.},\n    publisher = {IEEE},\n    keywords = {speech analysis, kernel fusion, emotion recognition},\n}\n\n
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\n As speech interfaces are getting richer and widespread, speech emotion recognition promises more attractive applications. In the continuous emotion recognition (CER) problem, tracking changes across affective states is an essential and desired capability. Although CER studies widely use correlation metrics in evaluations, these metrics do not always capture all the high-intensity changes in the affective domain. In this paper, we define a novel affective burst detection problem to capture high-intensity changes of the affective attributes accurately. We formulate a two-class classification approach to isolate affective burst regions over the affective state contour for this problem. The proposed classifier is a kernel-fusion dilated convolutional neural network (KFDCNN) architecture driven by speech spectral features to segment the affective attribute contour into idle and burst sections. Experimental evaluations are performed on the RECOLA and CreativeIT datasets. The proposed KFDCNN outperforms baseline feedforward neural networks on both datasets.\n
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\n \n\n \n \n \n \n \n \n Mukayese: Turkish NLP Strikes Back.\n \n \n \n \n\n\n \n Safaya, A.; Kurtuluş, E.; Goktogan, A.; and Yuret, D.\n\n\n \n\n\n\n In Findings of the Association for Computational Linguistics: ACL 2022, pages 846–863, Dublin, Ireland, May 2022. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"Mukayese:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{safaya-etal-2022-mukayese,\n    title = {Mukayese: {T}urkish {NLP} Strikes Back},\n    author = {Safaya, Ali and Kurtulu{\\c{s}}, Emirhan and Goktogan, Arda and Yuret, Deniz},\n    booktitle = {Findings of the Association for Computational Linguistics: ACL 2022},\n    month = {May},\n    year = {2022},\n    address = {Dublin, Ireland},\n    publisher = {Association for Computational Linguistics},\n    url = {https://aclanthology.org/2022.findings-acl.69},\n    doi = {10.18653/v1/2022.findings-acl.69},\n    pages = {846--863},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n \n Use of Affective Visual Information for Summarization of Human-Centric Videos.\n \n \n \n \n\n\n \n Köprü, B.; and Erzin, E.\n\n\n \n\n\n\n CoRR,1-14. 2022.\n \n\n\n\n
\n\n\n\n \n \n \"UsePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2107-03783,\n    author = {Berkay K{\\"{o}}pr{\\"{u}} and Engin Erzin},\n    title = {Use of Affective Visual Information for Summarization of Human-Centric Videos},\n    journal = {CoRR},\n    year = {2022},\n    abstract = {The increasing volume of user-generated human-centric video content and its applications, such as video retrieval and browsing, require compact representations addressed by the video summarization literature. Current supervised studies formulate video summarization as a sequence-to-sequence learning problem, and the existing solutions often neglect the surge of the human-centric view, which inherently contains affective content. In this study, we investigate the affective-information enriched supervised video summarization task for human-centric videos. First, we train a visual input-driven state-of-the-art continuous emotion recognition model (CER-NET) on the RECOLA dataset to estimate activation and valence attributes. Then, we integrate the estimated emotional attributes and their high-level embeddings from the CER-NET with the visual information to define the proposed affective video summarization (AVSUM) architectures. In addition, we investigate the use of attention to improve the AVSUM architectures and propose two new architectures based on temporal attention (TA-AVSUM) and spatial attention (SA-AVSUM). We conduct video summarization experiments on the TvSum and COGNIMUSE datasets. The proposed temporal attention-based TA-AVSUM architecture attains competitive video summarization performances with strong improvements for the human-centric videos compared to the state-of-the-art in terms of F-score, self-defined face recall, and rank correlation metrics.},\n    keywords = {CV,HCI},\n    pages = {1-14},\n    url = {https://ieeexplore.ieee.org/document/9954146},\n    doi = {10.1109/TAFFC.2022.3222882},\n    publisher = {IEEE},\n}\n\n
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\n The increasing volume of user-generated human-centric video content and its applications, such as video retrieval and browsing, require compact representations addressed by the video summarization literature. Current supervised studies formulate video summarization as a sequence-to-sequence learning problem, and the existing solutions often neglect the surge of the human-centric view, which inherently contains affective content. In this study, we investigate the affective-information enriched supervised video summarization task for human-centric videos. First, we train a visual input-driven state-of-the-art continuous emotion recognition model (CER-NET) on the RECOLA dataset to estimate activation and valence attributes. Then, we integrate the estimated emotional attributes and their high-level embeddings from the CER-NET with the visual information to define the proposed affective video summarization (AVSUM) architectures. In addition, we investigate the use of attention to improve the AVSUM architectures and propose two new architectures based on temporal attention (TA-AVSUM) and spatial attention (SA-AVSUM). We conduct video summarization experiments on the TvSum and COGNIMUSE datasets. The proposed temporal attention-based TA-AVSUM architecture attains competitive video summarization performances with strong improvements for the human-centric videos compared to the state-of-the-art in terms of F-score, self-defined face recall, and rank correlation metrics.\n
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\n \n\n \n \n \n \n \n UKP-SQUARE: An Online Platform for Question Answering Research.\n \n \n \n\n\n \n Baumgärtner, T.; Wang, K.; Sachdeva, R.; Eichler, M.; Geigle, G.; Poth, C.; Sterz, H.; Puerto, H.; Ribeiro, L. F.; Pfeiffer, J.; and others\n\n\n \n\n\n\n arXiv preprint arXiv:2203.13693. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{baumgartner2022ukp,\n    title = {UKP-SQUARE: An Online Platform for Question Answering Research},\n    author = {Baumg{\\"a}rtner, Tim and Wang, Kexin and Sachdeva, Rachneet and Eichler, Max and Geigle, Gregor and Poth, Clifton and Sterz, Hannah and Puerto, Haritz and Ribeiro, Leonardo FR and Pfeiffer, Jonas and others},\n    journal = {arXiv preprint arXiv:2203.13693},\n    year = {2022},\n}\n\n
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\n \n\n \n \n \n \n \n Leveraging semantic saliency maps for query-specific video summarization.\n \n \n \n\n\n \n Cizmeciler, K.; Erdem, E.; and Erdem, A.\n\n\n \n\n\n\n Multimedia Tools and Applications, 81(12): 17457–17482. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{cizmeciler2022leveraging,\n    title = {Leveraging semantic saliency maps for query-specific video summarization},\n    author = {Cizmeciler, Kemal and Erdem, Erkut and Erdem, Aykut},\n    journal = {Multimedia Tools and Applications},\n    volume = {81},\n    number = {12},\n    pages = {17457--17482},\n    year = {2022},\n    publisher = {Springer},\n}\n\n
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\n \n\n \n \n \n \n \n To augment or not to augment? A comparative study on text augmentation techniques for low-resource NLP.\n \n \n \n\n\n \n Şahin, G. G.\n\n\n \n\n\n\n Computational Linguistics, 48(1): 5–42. 2022.\n \n\n\n\n
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@article{csahin2022augment,\n    title = {To augment or not to augment? A comparative study on text augmentation techniques for low-resource NLP},\n    author = {{\\c{S}}ahin, G{\\"o}zde G{\\"u}l},\n    journal = {Computational Linguistics},\n    volume = {48},\n    number = {1},\n    pages = {5--42},\n    year = {2022},\n    publisher = {MIT Press},\n}\n\n
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\n \n\n \n \n \n \n \n FLAGS framework for comparative analysis of Federated Learning algorithms.\n \n \n \n\n\n \n Lodhi, A. H.; Akgün, B.; and Özkasap, Ö.\n\n\n \n\n\n\n Internet of Things, 20: 100638. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{lodhi2022flags,\n    title = {FLAGS framework for comparative analysis of Federated Learning algorithms},\n    author = {Lodhi, Ahnaf Hannan and Akg{\\"u}n, Bar{\\i}{\\c{s}} and {\\"O}zkasap, {\\"O}znur},\n    journal = {Internet of Things},\n    volume = {20},\n    pages = {100638},\n    year = {2022},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n Toward Detecting the Zone of Elite Tennis Players through Wearable Technology.\n \n \n \n\n\n \n Havlucu, H.; Akgun, B.; Eskenazi, T.; Coskun, A.; and Ozcan, O.\n\n\n \n\n\n\n Frontiers in Sports and Active Living, 4. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{havlucu2022toward,\n    title = {Toward Detecting the Zone of Elite Tennis Players through Wearable Technology},\n    author = {Havlucu, Hayati and Akgun, Baris and Eskenazi, Terry and Coskun, Aykut and Ozcan, Oguzhan},\n    journal = {Frontiers in Sports and Active Living},\n    volume = {4},\n    year = {2022},\n    publisher = {Frontiers Media SA},\n}\n\n
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\n \n\n \n \n \n \n \n An adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning.\n \n \n \n\n\n \n Guler, B.; Niaz, P. P; Madani, A.; Aydin, Y.; and Basdogan, C.\n\n\n \n\n\n\n Mechatronics, 86: 102851. 2022.\n \n\n\n\n
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@article{guler2022adaptive,\n    title = {An adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning},\n    author = {Guler, Berk and Niaz, Pouya P and Madani, Alireza and Aydin, Yusuf and Basdogan, Cagatay},\n    journal = {Mechatronics},\n    volume = {86},\n    pages = {102851},\n    year = {2022},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n Frequency-Dependent Behavior of Electrostatic Forces Between Human Finger and Touch Screen Under Electroadhesion.\n \n \n \n\n\n \n AliAbbasi, E.; Sormoli, M. A.; and Basdogan, C.\n\n\n \n\n\n\n IEEE Transactions on Haptics, 15(2): 416–428. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{aliabbasi2022frequency,\n    title = {Frequency-Dependent Behavior of Electrostatic Forces Between Human Finger and Touch Screen Under Electroadhesion},\n    author = {AliAbbasi, Easa and Sormoli, MReza Alipour and Basdogan, Cagatay},\n    journal = {IEEE Transactions on Haptics},\n    volume = {15},\n    number = {2},\n    pages = {416--428},\n    year = {2022},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n \n Exploration strategies for tactile graphics displayed by electrovibration on a touchscreen.\n \n \n \n \n\n\n \n Sadia, B.; Sadic, A.; Ayyildiz, M.; and Basdogan, C.\n\n\n \n\n\n\n International Journal of Human-Computer Studies, 160: 102760. 2022.\n \n\n\n\n
\n\n\n\n \n \n \"ExplorationPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@article{SADIA2022102760,\n    title = {Exploration strategies for tactile graphics displayed by electrovibration on a touchscreen},\n    journal = {International Journal of Human-Computer Studies},\n    volume = {160},\n    pages = {102760},\n    year = {2022},\n    issn = {1071-5819},\n    doi = {https://doi.org/10.1016/j.ijhcs.2021.102760},\n    url = {https://www.sciencedirect.com/science/article/pii/S1071581921001786},\n    author = {Bushra Sadia and Ayberk Sadic and Mehmet Ayyildiz and Cagatay Basdogan},\n    keywords = {Surface haptics,Electrovibration,Exploration strategies,Tactile perception,Haptic data,Haptic rendering,Friction modulation},\n    abstract = {test},\n}\n\n
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\n \n\n \n \n \n \n \n Kart-ON: An Extensible Paper Programming Strategy for Affordable Early Programming Education.\n \n \n \n\n\n \n Sabuncuoglu, A.; and Sezgin, T M.\n\n\n \n\n\n\n Proceedings of the ACM on Human-Computer Interaction, 6(EICS): 1–18. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{sabuncuoglu2022kart,\n    title = {Kart-ON: An Extensible Paper Programming Strategy for Affordable Early Programming Education},\n    author = {Sabuncuoglu, Alpay and Sezgin, T Metin},\n    journal = {Proceedings of the ACM on Human-Computer Interaction},\n    volume = {6},\n    number = {EICS},\n    pages = {1--18},\n    year = {2022},\n    publisher = {ACM New York, NY, USA},\n}\n\n
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\n \n\n \n \n \n \n \n Prototyping Products using Web-based AI Tools: Designing a Tangible Programming Environment with Children.\n \n \n \n\n\n \n Sabuncuoglu, A.; and Sezgin, T M.\n\n\n \n\n\n\n In 6th FabLearn Europe/MakeEd Conference 2022, pages 1–6, 2022. \n \n\n\n\n
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@inproceedings{sabuncuoglu2022prototyping,\n    title = {Prototyping Products using Web-based AI Tools: Designing a Tangible Programming Environment with Children},\n    author = {Sabuncuoglu, Alpay and Sezgin, T Metin},\n    booktitle = {6th FabLearn Europe/MakeEd Conference 2022},\n    pages = {1--6},\n    year = {2022},\n}\n\n
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\n \n\n \n \n \n \n \n Deep generation of 3D articulated models and animations from 2D stick figures.\n \n \n \n\n\n \n Akman, A.; Sahillioğlu, Y.; and Sezgin, T M.\n\n\n \n\n\n\n Computers & Graphics, 109: 65–74. 2022.\n \n\n\n\n
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@article{akman2022deep,\n    title = {Deep generation of 3D articulated models and animations from 2D stick figures},\n    author = {Akman, Alican and Sahillio{\\u{g}}lu, Yusuf and Sezgin, T Metin},\n    journal = {Computers \\& Graphics},\n    volume = {109},\n    pages = {65--74},\n    year = {2022},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n Training Socially Engaging Robots: Modeling Backchannel Behaviors with Batch Reinforcement Learning.\n \n \n \n\n\n \n Hussain, N.; Erzin, E.; Sezgin, T M.; and Yemez, Y.\n\n\n \n\n\n\n IEEE Transactions on Affective Computing, 13(4): 1840–1853. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{hussain2022training,\n    title = {Training Socially Engaging Robots: Modeling Backchannel Behaviors with Batch Reinforcement Learning},\n    author = {Hussain, Nusrah and Erzin, Engin and Sezgin, T Metin and Yemez, Y{\\"u}cel},\n    journal = {IEEE Transactions on Affective Computing},\n    volume = {13},\n    number = {4},\n    pages = {1840--1853},\n    year = {2022},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Gestural interaction in the kitchen: Insights into designing an interactive display controlled by hand specific on-skin gestures.\n \n \n \n\n\n \n Beşevli, C.; Genç, H. U.; Coşkun, A.; Göksun, T.; Yemez, Y.; and Özcan, O.\n\n\n \n\n\n\n The Design Journal, 25(3): 353–373. 2022.\n \n\n\n\n
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@article{becsevli2022gestural,\n    title = {Gestural interaction in the kitchen: Insights into designing an interactive display controlled by hand specific on-skin gestures},\n    author = {Be{\\c{s}}evli, Ceylan and Gen{\\c{c}}, H{\\"u}seyin U{\\u{g}}ur and Co{\\c{s}}kun, Aykut and G{\\"o}ksun, Tilbe and Yemez, Y{\\"u}cel and {\\"O}zcan, O{\\u{g}}uzhan},\n    journal = {The Design Journal},\n    volume = {25},\n    number = {3},\n    pages = {353--373},\n    year = {2022},\n    publisher = {Taylor \\& Francis},\n}\n\n
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\n \n\n \n \n \n \n \n m-rendezvous: Multi-agent asynchronous rendezvous search technique.\n \n \n \n\n\n \n Ozsoyeller, D.; Özkasap, Ö.; and Aloqaily, M.\n\n\n \n\n\n\n Future Generation Computer Systems, 126: 185–195. 2022.\n \n\n\n\n
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@article{ozsoyeller2022m,\n    title = {m-rendezvous: Multi-agent asynchronous rendezvous search technique},\n    author = {Ozsoyeller, Deniz and {\\"O}zkasap, {\\"O}znur and Aloqaily, Moayad},\n    journal = {Future Generation Computer Systems},\n    volume = {126},\n    pages = {185--195},\n    year = {2022},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n Federatedgrids: Federated learning and blockchain-assisted p2p energy sharing.\n \n \n \n\n\n \n Bouachir, O.; Aloqaily, M.; Özkasap, Ö.; and Ali, F.\n\n\n \n\n\n\n IEEE Transactions on Green Communications and Networking, 6(1): 424–436. 2022.\n \n\n\n\n
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@article{bouachir2022federatedgrids,\n    title = {Federatedgrids: Federated learning and blockchain-assisted p2p energy sharing},\n    author = {Bouachir, Ouns and Aloqaily, Moayad and {\\"O}zkasap, {\\"O}znur and Ali, Faizan},\n    journal = {IEEE Transactions on Green Communications and Networking},\n    volume = {6},\n    number = {1},\n    pages = {424--436},\n    year = {2022},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n SynergyGrids: blockchain-supported distributed microgrid energy trading.\n \n \n \n\n\n \n Aloqaily, M.; Bouachir, O.; Özkasap, Ö.; and Ali, F. S.\n\n\n \n\n\n\n Peer-to-Peer Networking and Applications, 15(2): 884–900. 2022.\n \n\n\n\n
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@article{aloqaily2022synergygrids,\n    title = {SynergyGrids: blockchain-supported distributed microgrid energy trading},\n    author = {Aloqaily, Moayad and Bouachir, Ouns and {\\"O}zkasap, {\\"O}znur and Ali, Faizan Safdar},\n    journal = {Peer-to-Peer Networking and Applications},\n    volume = {15},\n    number = {2},\n    pages = {884--900},\n    year = {2022},\n    publisher = {Springer},\n}\n\n
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@article{hayyolalam2022dynamic,\n    title = {Dynamic QoS/QoE-aware reliable service composition framework for edge intelligence},\n    author = {Hayyolalam, Vahideh and Otoum, Safa and {\\"O}zkasap, {\\"O}znur},\n    journal = {Cluster Computing},\n    volume = {25},\n    number = {3},\n    pages = {1695--1713},\n    year = {2022},\n    publisher = {Springer},\n}\n\n
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@inproceedings{seven2022exploratory,\n    title = {EXPLORATORY ANALYSES OF SYMPTOM CLUSTER CHANGE DURING CHEMOTHERAPY IN WOMEN WITH BREAST CANCER RECEIVING CHEMOTHERAPY},\n    author = {Seven, Memnun and Bagcivan, Gulcan and Pasalak, Seyma Inciser and Ozkasap, Oznur and Selcukbiricik, Fatih},\n    booktitle = {ONCOLOGY NURSING FORUM},\n    volume = {49},\n    number = {2},\n    pages = {62--62},\n    year = {2022},\n    organization = {ONCOLOGY NURSING SOC 125 ENTERPRISE DR, PITTSBURGH, PA 15275 USA},\n}\n\n
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@article{lim2022artificial,\n    title = {Artificial intelligence approaches to human-microbiome protein--protein interactions},\n    author = {Lim, Hansaim and Cankara, Fatma and Tsai, Chung-Jung and Keskin, Ozlem and Nussinov, Ruth and Gursoy, Attila},\n    journal = {Current Opinion in Structural Biology},\n    volume = {73},\n    pages = {102328},\n    year = {2022},\n    publisher = {Elsevier},\n}\n\n
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@article{ovek2022sars,\n    title = {SARS-CoV-2 interactome 3D: a web interface for 3D visualization and analysis of SARS-CoV-2--human mimicry and interactions},\n    author = {Ovek, Damla and Taweel, Ameer and Abali, Zeynep and Tezsezen, Ece and Koroglu, Yunus Emre and Tsai, Chung-Jung and Nussinov, Ruth and Keskin, Ozlem and Gursoy, Attila},\n    journal = {Bioinformatics},\n    volume = {38},\n    number = {5},\n    pages = {1455--1457},\n    year = {2022},\n    publisher = {Oxford University Press},\n}\n\n
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@article{ovek2022artificial,\n    title = {Artificial intelligence based methods for hot spot prediction},\n    author = {Ovek, Damla and Abali, Zeynep and Zeylan, Melisa Ece and Keskin, Ozlem and Gursoy, Attila and Tuncbag, Nurcan},\n    journal = {Current Opinion in Structural Biology},\n    volume = {72},\n    pages = {209--218},\n    year = {2022},\n    publisher = {Elsevier},\n}\n\n
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@article{tekalp2022deep,\n    title = {Deep Learning for Image/Video Restoration and Super-resolution},\n    author = {Tekalp, A Murat and others},\n    journal = {Foundations and Trends{\\textregistered} in Computer Graphics and Vision},\n    volume = {13},\n    number = {1},\n    pages = {1--110},\n    year = {2022},\n    publisher = {Now Publishers, Inc.},\n}\n\n
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@article{erdem2022neural,\n    title = {Neural natural language generation: A survey on multilinguality, multimodality, controllability and learning},\n    author = {Erdem, Erkut and Kuyu, Menekse and Yagcioglu, Semih and Frank, Anette and Parcalabescu, Letitia and Plank, Barbara and Babii, Andrii and Turuta, Oleksii and Erdem, Aykut and Calixto, Iacer and others},\n    journal = {Journal of Artificial Intelligence Research},\n    volume = {73},\n    pages = {1131--1207},\n    year = {2022},\n}\n\n
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@article{bozkurt2022correlative,\n    title = {Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation},\n    author = {Bozkurt, Bariscan and Isfendiyaroglu, Ates and Pehlevan, Cengiz and Erdogan, Alper T},\n    journal = {arXiv preprint arXiv:2210.04222},\n    year = {2022},\n}\n\n
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@article{ozsoy2022self,\n    title = {Self-supervised learning with an information maximization criterion},\n    author = {Ozsoy, Serdar and Hamdan, Shadi and Arik, Sercan and Yuret, Deniz and Erdogan, Alper},\n    journal = {Advances in Neural Information Processing Systems},\n    volume = {35},\n    pages = {35240--35253},\n    year = {2022},\n}\n\n
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@article{bozkurt2022biologically,\n    title = {Biologically-plausible determinant maximization neural networks for blind separation of correlated sources},\n    author = {Bozkurt, Bariscan and Pehlevan, Cengiz and Erdogan, Alper},\n    journal = {Advances in Neural Information Processing Systems},\n    volume = {35},\n    pages = {13704--13717},\n    year = {2022},\n}\n\n
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@inproceedings{erdogan2022information,\n    title = {An information maximization based blind source separation approach for dependent and independent sources},\n    author = {Erdogan, Alper T},\n    booktitle = {ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    pages = {4378--4382},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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@inproceedings{bozkurt2022identifiable,\n    title = {On identifiable polytope characterization for polytopic matrix factorization},\n    author = {Bozkurt, Bariscan and Erdogan, Alper T},\n    booktitle = {ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    pages = {3343--3347},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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@article{kesen2022detecting,\n    title = {Detecting Euphemisms with Literal Descriptions and Visual Imagery},\n    author = {Kesen, {\\.I}lker and Erdem, Aykut and Erdem, Erkut and Calixto, Iacer},\n    journal = {arXiv preprint arXiv:2211.04576},\n    year = {2022},\n}\n\n
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@article{karacan2022disentangling,\n    title = {Disentangling Content and Motion for Text-Based Neural Video Manipulation},\n    author = {Karacan, Levent and Kerimo{\\u{g}}lu, Tolga and {\\.I}nan, {\\.I}smail and Birdal, Tolga and Erdem, Erkut and Erdem, Aykut},\n    journal = {arXiv preprint arXiv:2211.02980},\n    year = {2022},\n}\n\n
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@inproceedings{kesen2022modulating,\n    title = {Modulating Bottom-Up and Top-Down Visual Processing via Language-Conditional Filters},\n    author = {Kesen, Ilker and Can, Ozan Arkan and Erdem, Erkut and Erdem, Aykut and Y{\\"u}ret, Deniz},\n    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},\n    pages = {4610--4620},\n    year = {2022},\n}\n\n
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@inproceedings{dalmaz2022multi,\n    title = {Multi-Contrast MRI Synthesis with Channel-Exchanging-Network},\n    author = {Dalmaz, Onat and Aytekin, Idil and Dar, Salman Ul Hassan and Erdem, Aykut and Erdem, Erkut and Cukur, Tolga},\n    booktitle = {2022 30th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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@inproceedings{madani2022robot,\n    title = {Robot-Assisted Drilling on Curved Surfaces with Haptic Guidance under Adaptive Admittance Control},\n    author = {Madani, Alireza and Niaz, Pouya P and Guler, Berk and Aydin, Yusuf and Basdogan, Cagatay},\n    booktitle = {2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},\n    pages = {3723--3730},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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@inproceedings{emirdaugi2022detection,\n    title = {Detection of Stride Time and Stance Phase Ratio from Accelerometer Data for Gait Analysis},\n    author = {Emirda{\\u{g}}{\\i}, Ahmet Rasim and Tokmak, Fadime and K{\\"o}pr{\\"u}c{\\"u}, Nursena and Akar, Kardelen and Vural, Atay and Erzin, Engin},\n    booktitle = {2022 30th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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@inproceedings{kopru2022affective,\n    title = {Affective Burst Detection from Speech using Kernel-fusion Dilated Convolutional Neural Networks},\n    author = {K{\\"o}pr{\\"u}, Berkay and Erzin, Engin},\n    booktitle = {2022 30th European Signal Processing Conference (EUSIPCO)},\n    pages = {105--109},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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@inproceedings{akan2022stretchbev,\n    title = {Stretchbev: Stretching future instance prediction spatially and temporally},\n    author = {Akan, Adil Kaan and G{\\"u}ney, Fatma},\n    booktitle = {Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part XXXVIII},\n    pages = {444--460},\n    year = {2022},\n    organization = {Springer},\n}\n\n
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@inproceedings{ulas2022flexible,\n    title = {Flexible luma-chroma bit allocation in learned image compression for high-fidelity sharper images},\n    author = {Ulas, O Ugur and Tekalp, A Murat},\n    booktitle = {2022 Picture Coding Symposium (PCS)},\n    pages = {31--35},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Mixed and Multi-Precision SpMV for GPUs with Row-wise Precision Selection.\n \n \n \n\n\n \n Tezcan, E.; Torun, T.; Koşar, F.; Kaya, K.; and Unat, D.\n\n\n \n\n\n\n In 2022 IEEE 34th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), pages 31–40, 2022. IEEE\n \n\n\n\n
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@inproceedings{tezcan2022mixed,\n    title = {Mixed and Multi-Precision SpMV for GPUs with Row-wise Precision Selection},\n    author = {Tezcan, Erhan and Torun, Tugba and Ko{\\c{s}}ar, Fahrican and Kaya, Kamer and Unat, Didem},\n    booktitle = {2022 IEEE 34th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)},\n    pages = {31--40},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Multi-Field De-Interlacing Using Deformable Convolution Residual Blocks and Self-Attention.\n \n \n \n\n\n \n Ji, R.; and Tekalp, A M.\n\n\n \n\n\n\n In 2022 IEEE International Conference on Image Processing (ICIP), pages 901–905, 2022. IEEE\n \n\n\n\n
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@inproceedings{ji2022multi,\n    title = {Multi-Field De-Interlacing Using Deformable Convolution Residual Blocks and Self-Attention},\n    author = {Ji, Ronglei and Tekalp, A Murat},\n    booktitle = {2022 IEEE International Conference on Image Processing (ICIP)},\n    pages = {901--905},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Flexible-Rate Learned Hierarchical Bi-Directional Video Compression With Motion Refinement and Frame-Level Bit Allocation.\n \n \n \n\n\n \n Çetin, E.; Yılmaz, M A.; and Tekalp, A M.\n\n\n \n\n\n\n In 2022 IEEE International Conference on Image Processing (ICIP), pages 1206–1210, 2022. IEEE\n \n\n\n\n
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@inproceedings{ccetin2022flexible,\n    title = {Flexible-Rate Learned Hierarchical Bi-Directional Video Compression With Motion Refinement and Frame-Level Bit Allocation},\n    author = {{\\c{C}}etin, Eren and Y{\\i}lmaz, M Ak{\\i}n and Tekalp, A Murat},\n    booktitle = {2022 IEEE International Conference on Image Processing (ICIP)},\n    pages = {1206--1210},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n MMSR: Multiple-Model Learned Image Super-Resolution Benefiting from Class-Specific Image Priors.\n \n \n \n\n\n \n Korkmaz, C.; Tekalp, A M.; and Doğan, Z.\n\n\n \n\n\n\n In 2022 IEEE International Conference on Image Processing (ICIP), pages 2816–2820, 2022. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{korkmaz2022mmsr,\n    title = {MMSR: Multiple-Model Learned Image Super-Resolution Benefiting from Class-Specific Image Priors},\n    author = {Korkmaz, Cansu and Tekalp, A Murat and Do{\\u{g}}an, Zafer},\n    booktitle = {2022 IEEE International Conference on Image Processing (ICIP)},\n    pages = {2816--2820},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Perception-Distortion Trade-Off in the SR Space Spanned by Flow Models.\n \n \n \n\n\n \n Korkmaz, C.; Tekalp, A M.; Doğan, Z.; Erdem, E.; and Erdem, A.\n\n\n \n\n\n\n In 2022 IEEE International Conference on Image Processing (ICIP), pages 2396–2400, 2022. IEEE\n \n\n\n\n
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@inproceedings{korkmaz2022perception,\n    title = {Perception-Distortion Trade-Off in the SR Space Spanned by Flow Models},\n    author = {Korkmaz, Cansu and Tekalp, A Murat and Do{\\u{g}}an, Zafer and Erdem, Erkut and Erdem, Aykut},\n    booktitle = {2022 IEEE International Conference on Image Processing (ICIP)},\n    pages = {2396--2400},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n DHT-based edge and fog computing systems: infrastructures and applications.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Taheri-Boshrooyeh, S.; and Özkasap, Ö.\n\n\n \n\n\n\n In IEEE INFOCOM 2022-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pages 1–6, 2022. IEEE\n \n\n\n\n
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@inproceedings{hassanzadeh2022dht,\n    title = {DHT-based edge and fog computing systems: infrastructures and applications},\n    author = {Hassanzadeh-Nazarabadi, Yahya and Taheri-Boshrooyeh, Sanaz and {\\"O}zkasap, {\\"O}znur},\n    booktitle = {IEEE INFOCOM 2022-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)},\n    pages = {1--6},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n A Hybrid Edge-assisted Machine Learning Approach for Detecting Heart Disease.\n \n \n \n\n\n \n Hayyolalam, V.; Otoum, S.; and Özkasap, Ö.\n\n\n \n\n\n\n In ICC 2022-IEEE International Conference on Communications, pages 2966–2971, 2022. IEEE\n \n\n\n\n
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@inproceedings{hayyolalam2022hybrid,\n    title = {A Hybrid Edge-assisted Machine Learning Approach for Detecting Heart Disease},\n    author = {Hayyolalam, Vahideh and Otoum, Safa and {\\"O}zkasap, {\\"O}znur},\n    booktitle = {ICC 2022-IEEE International Conference on Communications},\n    pages = {2966--2971},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Multi3Generation: Multitask, Multilingual, Multimodal Language Generation.\n \n \n \n\n\n \n Barreiro, A.; de Souza, J. G.; Gatt, A.; Bhatt, M.; Lloret, E.; Erdem, A.; Gkatzia, D.; Moniz, H.; Russo, I.; Kepler, F.; and others\n\n\n \n\n\n\n In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 345–346, 2022. \n \n\n\n\n
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@inproceedings{barreiro2022multi3generation,\n    title = {Multi3Generation: Multitask, Multilingual, Multimodal Language Generation},\n    author = {Barreiro, Anabela and de Souza, Jos{\\'e} GC and Gatt, Albert and Bhatt, Mehul and Lloret, Elena and Erdem, Aykut and Gkatzia, Dimitra and Moniz, Helena and Russo, Irene and Kepler, Fabio and others},\n    booktitle = {Proceedings of the 23rd Annual Conference of the European Association for Machine Translation},\n    pages = {345--346},\n    year = {2022},\n}\n\n
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\n \n\n \n \n \n \n \n Henle fiber layer mapping with directional optical coherence tomography.\n \n \n \n\n\n \n Kesim, C.; Bektas, S. N.; Kulali, Z.; Yildiz, E.; Ersoz, M G.; Sahin, A.; Gunduz-Demir, C.; and Hasanreisoglu, M.\n\n\n \n\n\n\n Retina, 42(9): 1780–1787. 2022.\n \n\n\n\n
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@article{kesim2022henle,\n    title = {Henle fiber layer mapping with directional optical coherence tomography},\n    author = {Kesim, Cem and Bektas, Sevval Nur and Kulali, Zeynep and Yildiz, Erdost and Ersoz, M Giray and Sahin, Afsun and Gunduz-Demir, Cigdem and Hasanreisoglu, Murat},\n    journal = {Retina},\n    volume = {42},\n    number = {9},\n    pages = {1780--1787},\n    year = {2022},\n    publisher = {Wolters Kluwer},\n}\n\n
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\n \n\n \n \n \n \n \n Banking Order Classification and Information Extraction.\n \n \n \n\n\n \n Bakır, V. O.; Çağatay, İ.; Güven, M.; Koraş, M.; Gönen, M.; and Akgün, B.\n\n\n \n\n\n\n In 2022 30th Signal Processing and Communications Applications Conference (SIU), pages 1–4, 2022. IEEE\n \n\n\n\n
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@inproceedings{bakir2022banking,\n    title = {Banking Order Classification and Information Extraction},\n    author = {Bak{\\i}r, Veli O{\\u{g}}uzalp and {\\c{C}}a{\\u{g}}atay, {\\.I}lhan and G{\\"u}ven, Melih and Kora{\\c{s}}, Murat and G{\\"o}nen, Mehmet and Akg{\\"u}n, Bar{\\i}{\\c{s}}},\n    booktitle = {2022 30th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2022},\n    organization = {IEEE},\n}\n\n
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\n  \n 2021\n \n \n (58)\n \n \n
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\n \n\n \n \n \n \n \n Effect of Remote Masking on Tactile Perception of Electrovibration.\n \n \n \n\n\n \n Jamalzadeh, M.; Basdogan, C.; and Güçlü, B.\n\n\n \n\n\n\n IEEE Transactions on Haptics, 14(1): 132-142. 2021.\n \n\n\n\n
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@article{9204403,\n    author = {Jamalzadeh, Milad and Basdogan, Cagatay and G{\\"u}{\\c{c}}l{\\"u}, Burak},\n    journal = {IEEE Transactions on Haptics},\n    title = {Effect of Remote Masking on Tactile Perception of Electrovibration},\n    year = {2021},\n    volume = {14},\n    number = {1},\n    pages = {132-142},\n    doi = {10.1109/TOH.2020.3025772}}
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\n \n\n \n \n \n \n \n Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression.\n \n \n \n\n\n \n Tekalp, A. M.; Covell, M.; Timofte, R.; and Dong, C.\n\n\n \n\n\n\n 2021.\n \n\n\n\n
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@misc{tekalp2021editorial,\n    author = {A. Murat Tekalp and Michele Covell and Radu Timofte and Chao Dong},\n    title = {Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression},\n    year = {2021},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Edge Intelligence for Empowering IoT-based Healthcare Systems.\n \n \n \n\n\n \n Hayyolalam, V.; Aloqaily, M.; Ozkasap, O.; and Guizani, M.\n\n\n \n\n\n\n 2021.\n \n\n\n\n
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@misc{hayyolalam2021edge,\n    title = {Edge Intelligence for Empowering IoT-based Healthcare Systems},\n    author = {Vahideh Hayyolalam and Moayad Aloqaily and Oznur Ozkasap and Mohsen Guizani},\n    year = {2021},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n \n The structural basis of Akt PH domain interaction with calmodulin.\n \n \n \n \n\n\n \n Weako, J.; Jang, H.; Keskin, O.; Nussinov, R.; and Gursoy, A.\n\n\n \n\n\n\n Biophysical Journal. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{WEAKO2021,\n    title = {The structural basis of Akt PH domain interaction with calmodulin},\n    journal = {Biophysical Journal},\n    year = {2021},\n    issn = {0006-3495},\n    doi = {https://doi.org/10.1016/j.bpj.2021.03.018},\n    url = {https://www.sciencedirect.com/science/article/pii/S0006349521002484},\n    author = {Jackson Weako and Hyunbum Jang and Ozlem Keskin and Ruth Nussinov and Attila Gursoy},\n    abstract = {Akt plays a key role in the Ras/PI3K/Akt/mTOR signaling pathway. In breast cancer, Akt translocation to the plasma membrane is enabled by the interaction of its pleckstrin homology domain (PHD) with calmodulin (CaM). At the membrane, the conformational change promoted by PIP3 releases CaM and facilitates Thr308 and Ser473 phosphorylation and activation. Here, using modeling and molecular dynamics simulations, we aim to figure out how CaM interacts with Akt’s PHD at the atomic level. Our simulations show that CaM-PHD interaction is thermodynamically stable and involves a β-strand rather than an α-helix, in agreement with NMR data, and that electrostatic and hydrophobic interactions are critical. The PHD interacts with CaM lobes; however, multiple modes are possible. IP4, the polar head of PIP3, weakens the CaM-PHD interaction, implicating the release mechanism at the plasma membrane. Recently, we unraveled the mechanism of PI3Kα activation at the atomistic level and the structural basis for Ras role in the activation. Here, our atomistic structural data clarify the mechanism of how CaM interacts, delivers, and releases Akt—the next node in the Ras/PI3K pathway—at the plasma membrane.},\n    keywords = {CBM},\n}\n\n
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\n Akt plays a key role in the Ras/PI3K/Akt/mTOR signaling pathway. In breast cancer, Akt translocation to the plasma membrane is enabled by the interaction of its pleckstrin homology domain (PHD) with calmodulin (CaM). At the membrane, the conformational change promoted by PIP3 releases CaM and facilitates Thr308 and Ser473 phosphorylation and activation. Here, using modeling and molecular dynamics simulations, we aim to figure out how CaM interacts with Akt’s PHD at the atomic level. Our simulations show that CaM-PHD interaction is thermodynamically stable and involves a β-strand rather than an α-helix, in agreement with NMR data, and that electrostatic and hydrophobic interactions are critical. The PHD interacts with CaM lobes; however, multiple modes are possible. IP4, the polar head of PIP3, weakens the CaM-PHD interaction, implicating the release mechanism at the plasma membrane. Recently, we unraveled the mechanism of PI3Kα activation at the atomistic level and the structural basis for Ras role in the activation. Here, our atomistic structural data clarify the mechanism of how CaM interacts, delivers, and releases Akt—the next node in the Ras/PI3K pathway—at the plasma membrane.\n
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\n \n\n \n \n \n \n \n \n Neuropsychiatric Symptoms of COVID-19 Explained by SARS-CoV-2 Proteins’ Mimicry of Human Protein Interactions.\n \n \n \n \n\n\n \n Yapici-Eser, H.; Koroglu, Y. E.; Oztop-Cakmak, O.; Keskin, O.; Gursoy, A.; and Gursoy-Ozdemir, Y.\n\n\n \n\n\n\n Frontiers in Human Neuroscience, 15: 126. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"NeuropsychiatricPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{10.3389/fnhum.2021.656313,\n    author = {Yapici-Eser, Hale and Koroglu, Yunus Emre and Oztop-Cakmak, Ozgur and Keskin, Ozlem and Gursoy, Attila and Gursoy-Ozdemir, Yasemin},\n    title = {Neuropsychiatric Symptoms of COVID-19 Explained by SARS-CoV-2 Proteins’ Mimicry of Human Protein Interactions},\n    journal = {Frontiers in Human Neuroscience},\n    volume = {15},\n    pages = {126},\n    year = {2021},\n    url = {https://www.frontiersin.org/article/10.3389/fnhum.2021.656313},\n    doi = {10.3389/fnhum.2021.656313},\n    issn = {1662-5161},\n    abstract = {The first clinical symptoms focused on the presentation of coronavirus disease 2019 (COVID-19) have been respiratory failure, however, accumulating evidence also points to its presentation with neuropsychiatric symptoms, the exact mechanisms of which are not well known. By using a computational methodology, we aimed to explain the molecular paths of COVID-19 associated neuropsychiatric symptoms, based on the mimicry of the human protein interactions with SARS-CoV-2 proteins.Methods: Available 11 of the 29 SARS-CoV-2 proteins’ structures have been extracted from Protein Data Bank. HMI-PRED (Host-Microbe Interaction PREDiction), a recently developed web server for structural PREDiction of protein-protein interactions (PPIs) between host and any microbial species, was used to find the “interface mimicry” through which the microbial proteins hijack host binding surfaces. Classification of the found interactions was conducted using the PANTHER Classification System.Results: Predicted Human-SARS-CoV-2 protein interactions have been extensively compared with the literature. Based on the analysis of the molecular functions, cellular localizations and pathways related to human proteins, SARS-CoV-2 proteins are found to possibly interact with human proteins linked to synaptic vesicle trafficking, endocytosis, axonal transport, neurotransmission, growth factors, mitochondrial and blood-brain barrier elements, in addition to its peripheral interactions with proteins linked to thrombosis, inflammation and metabolic control.Conclusion: SARS-CoV-2-human protein interactions may lead to the development of delirium, psychosis, seizures, encephalitis, stroke, sensory impairments, peripheral nerve diseases, and autoimmune disorders. Our findings are also supported by the previous in vivo and in vitro studies from other viruses. Further in vivo and in vitro studies using the proteins that are pointed here, could pave new targets both for avoiding and reversing neuropsychiatric presentations.},\n    keywords = {CBM},\n}\n\n
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\n The first clinical symptoms focused on the presentation of coronavirus disease 2019 (COVID-19) have been respiratory failure, however, accumulating evidence also points to its presentation with neuropsychiatric symptoms, the exact mechanisms of which are not well known. By using a computational methodology, we aimed to explain the molecular paths of COVID-19 associated neuropsychiatric symptoms, based on the mimicry of the human protein interactions with SARS-CoV-2 proteins.Methods: Available 11 of the 29 SARS-CoV-2 proteins’ structures have been extracted from Protein Data Bank. HMI-PRED (Host-Microbe Interaction PREDiction), a recently developed web server for structural PREDiction of protein-protein interactions (PPIs) between host and any microbial species, was used to find the “interface mimicry” through which the microbial proteins hijack host binding surfaces. Classification of the found interactions was conducted using the PANTHER Classification System.Results: Predicted Human-SARS-CoV-2 protein interactions have been extensively compared with the literature. Based on the analysis of the molecular functions, cellular localizations and pathways related to human proteins, SARS-CoV-2 proteins are found to possibly interact with human proteins linked to synaptic vesicle trafficking, endocytosis, axonal transport, neurotransmission, growth factors, mitochondrial and blood-brain barrier elements, in addition to its peripheral interactions with proteins linked to thrombosis, inflammation and metabolic control.Conclusion: SARS-CoV-2-human protein interactions may lead to the development of delirium, psychosis, seizures, encephalitis, stroke, sensory impairments, peripheral nerve diseases, and autoimmune disorders. Our findings are also supported by the previous in vivo and in vitro studies from other viruses. Further in vivo and in vitro studies using the proteins that are pointed here, could pave new targets both for avoiding and reversing neuropsychiatric presentations.\n
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\n \n\n \n \n \n \n \n Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art.\n \n \n \n\n\n \n Janai, J.; Güney, F.; Behl, A.; and Geiger, A.\n\n\n \n\n\n\n 2021.\n \n\n\n\n
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@misc{janai2021computer,\n    title = {Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art},\n    author = {Joel Janai and Fatma G{\\"u}ney and Aseem Behl and Andreas Geiger},\n    year = {2021},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n \n Improving phoneme recognition of throat microphone speech recordings using transfer learning.\n \n \n \n \n\n\n \n Turan, M. T.; and Erzin, E.\n\n\n \n\n\n\n Speech Communication, 129: 25-32. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"ImprovingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@article{TURAN202125,\n    title = {Improving phoneme recognition of throat microphone speech recordings using transfer learning},\n    journal = {Speech Communication},\n    volume = {129},\n    pages = {25-32},\n    year = {2021},\n    issn = {0167-6393},\n    doi = {https://doi.org/10.1016/j.specom.2021.02.004},\n    url = {https://www.sciencedirect.com/science/article/pii/S0167639321000200},\n    author = {M.A. Tu{\\u{g}}tekin Turan and Engin Erzin},\n    keywords = {Phoneme recognition,Feature augmentation,Transfer learning,Throat microphone,Denoising auto-encoder,MSP},\n    abstract = {Throat microphones (TM) are a type of skin-attached non-acoustic sensors, which are robust to environmental noise but carry a lower signal bandwidth characterization than the traditional close-talk microphones (CM). Attaining high-performance phoneme recognition is a challenging task when the training data from a degrading channel, such as TM, is limited. In this paper, we address this challenge for the TM speech recordings using a transfer learning approach based on the stacked denoising auto-encoders (SDA). The proposed transfer learning approach defines an SDA-based domain adaptation framework to map the source domain CM representations and the target domain TM representations into a common latent space, where the mismatch across TM and CM is eliminated to better train an acoustic model and to improve the TM phoneme recognition. For the phoneme recognition task, we use the convolutional neural network (CNN) and the hidden Markov model (HMM) based CNN/HMM hybrid system, which delivers better acoustic modeling performance compared to the conventional Gaussian mixture model (GMM) based models. In the experimental evaluations, we observed more than 12% relative phoneme error rate (PER) improvement for the TM recordings with the proposed transfer learning approach compared to baseline performances.},\n    publisher = {Elsevier B.V. },\n}\n\n
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\n Throat microphones (TM) are a type of skin-attached non-acoustic sensors, which are robust to environmental noise but carry a lower signal bandwidth characterization than the traditional close-talk microphones (CM). Attaining high-performance phoneme recognition is a challenging task when the training data from a degrading channel, such as TM, is limited. In this paper, we address this challenge for the TM speech recordings using a transfer learning approach based on the stacked denoising auto-encoders (SDA). The proposed transfer learning approach defines an SDA-based domain adaptation framework to map the source domain CM representations and the target domain TM representations into a common latent space, where the mismatch across TM and CM is eliminated to better train an acoustic model and to improve the TM phoneme recognition. For the phoneme recognition task, we use the convolutional neural network (CNN) and the hidden Markov model (HMM) based CNN/HMM hybrid system, which delivers better acoustic modeling performance compared to the conventional Gaussian mixture model (GMM) based models. In the experimental evaluations, we observed more than 12% relative phoneme error rate (PER) improvement for the TM recordings with the proposed transfer learning approach compared to baseline performances.\n
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\n \n\n \n \n \n \n \n \n mustGAN: multi-stream Generative Adversarial Networks for MR Image Synthesis.\n \n \n \n \n\n\n \n Yurt, M.; Dar, S. U.; Erdem, A.; Erdem, E.; Oguz, K. K; and Çukur, T.\n\n\n \n\n\n\n Medical Image Analysis, 70: 101944. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"mustGAN:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 13 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{YURT2021101944,\n    title = {mustGAN: multi-stream Generative Adversarial Networks for MR Image Synthesis},\n    journal = {Medical Image Analysis},\n    volume = {70},\n    pages = {101944},\n    year = {2021},\n    issn = {1361-8415},\n    doi = {https://doi.org/10.1016/j.media.2020.101944},\n    url = {https://www.sciencedirect.com/science/article/pii/S136184152030308X},\n    author = {Mahmut Yurt and Salman UH Dar and Aykut Erdem and Erkut Erdem and Kader K Oguz and Tolga {\\c{C}}ukur},\n    keywords = {Magnetic resonance imaging (MRI),Multi-contrast,Generative adversarial networks (GAN),Image synthesis,Multi-stream,Fusion,CV},\n    abstract = {Multi-contrast MRI protocols increase the level of morphological information available for diagnosis. Yet, the number and quality of contrasts are limited in practice by various factors including scan time and patient motion. Synthesis of missing or corrupted contrasts from other high-quality ones can alleviate this limitation. When a single target contrast is of interest, common approaches for multi-contrast MRI involve either one-to-one or many-to-one synthesis methods depending on their input. One-to-one methods take as input a single source contrast, and they learn a latent representation sensitive to unique features of the source. Meanwhile, many-to-one methods receive multiple distinct sources, and they learn a shared latent representation more sensitive to common features across sources. For enhanced image synthesis, we propose a multi-stream approach that aggregates information across multiple source images via a mixture of multiple one-to-one streams and a joint many-to-one stream. The complementary feature maps generated in the one-to-one streams and the shared feature maps generated in the many-to-one stream are combined with a fusion block. The location of the fusion block is adaptively modified to maximize task-specific performance. Quantitative and radiological assessments on T1,- T2-, PD-weighted, and FLAIR images clearly demonstrate the superior performance of the proposed method compared to previous state-of-the-art one-to-one and many-to-one methods.},\n}\n\n
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\n Multi-contrast MRI protocols increase the level of morphological information available for diagnosis. Yet, the number and quality of contrasts are limited in practice by various factors including scan time and patient motion. Synthesis of missing or corrupted contrasts from other high-quality ones can alleviate this limitation. When a single target contrast is of interest, common approaches for multi-contrast MRI involve either one-to-one or many-to-one synthesis methods depending on their input. One-to-one methods take as input a single source contrast, and they learn a latent representation sensitive to unique features of the source. Meanwhile, many-to-one methods receive multiple distinct sources, and they learn a shared latent representation more sensitive to common features across sources. For enhanced image synthesis, we propose a multi-stream approach that aggregates information across multiple source images via a mixture of multiple one-to-one streams and a joint many-to-one stream. The complementary feature maps generated in the one-to-one streams and the shared feature maps generated in the many-to-one stream are combined with a fusion block. The location of the fusion block is adaptively modified to maximize task-specific performance. Quantitative and radiological assessments on T1,- T2-, PD-weighted, and FLAIR images clearly demonstrate the superior performance of the proposed method compared to previous state-of-the-art one-to-one and many-to-one methods.\n
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\n \n\n \n \n \n \n \n \n Generating visual story graphs with application to photo album summarization.\n \n \n \n \n\n\n \n Celikkale, B.; Erdogan, G.; Erdem, A.; and Erdem, E.\n\n\n \n\n\n\n Signal Processing: Image Communication, 90: 116033. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"GeneratingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 6 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{CELIKKALE2021116033,\n    title = {Generating visual story graphs with application to photo album summarization},\n    journal = {Signal Processing: Image Communication},\n    volume = {90},\n    pages = {116033},\n    year = {2021},\n    issn = {0923-5965},\n    doi = {https://doi.org/10.1016/j.image.2020.116033},\n    url = {https://www.sciencedirect.com/science/article/pii/S092359652030182X},\n    author = {Bora Celikkale and Goksu Erdogan and Aykut Erdem and Erkut Erdem},\n    keywords = {Visual story graph,Structured summarization,CV},\n    abstract = {Making sense of ever-growing amount of visual data available on the web is difficult, especially when considered in an unsupervised manner. As a step towards this goal, this study tackles a relatively less explored topic of generating structured summaries of large photo collections. Our framework relies on the notion of a story graph which captures the main narratives in the data and their relationships based on their visual, textual and spatio-temporal features. Its output is a directed graph with a set of possibly intersecting paths. Our proposed approach identifies coherent visual storylines and exploits sub-modularity to select a subset of these lines which covers the general narrative at most. Our experimental analysis reveals that extracted story graphs allow for obtaining better results when utilized as priors for photo album summarization. Moreover, our user studies show that our approach delivers better performance on next image prediction and coverage tasks than the state-of-the-art.},\n}\n\n
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\n Making sense of ever-growing amount of visual data available on the web is difficult, especially when considered in an unsupervised manner. As a step towards this goal, this study tackles a relatively less explored topic of generating structured summaries of large photo collections. Our framework relies on the notion of a story graph which captures the main narratives in the data and their relationships based on their visual, textual and spatio-temporal features. Its output is a directed graph with a set of possibly intersecting paths. Our proposed approach identifies coherent visual storylines and exploits sub-modularity to select a subset of these lines which covers the general narrative at most. Our experimental analysis reveals that extracted story graphs allow for obtaining better results when utilized as priors for photo album summarization. Moreover, our user studies show that our approach delivers better performance on next image prediction and coverage tasks than the state-of-the-art.\n
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\n \n\n \n \n \n \n \n \n Domain Adaptation for Food Intake Classification with Teacher/Student Learning.\n \n \n \n \n\n\n \n Turan, M. A. T.; and Erzin, E.\n\n\n \n\n\n\n IEEE Transactions on Multimedia, 23: 4220 - 4231. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"DomainPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{turan2020domain,\n    title = {Domain Adaptation for Food Intake Classification with Teacher/Student Learning},\n    author = {Turan, Mehmet Ali Tugtekin and Erzin, Engin},\n    journal = {IEEE Transactions on Multimedia},\n    publisher = {IEEE},\n    keywords = {MSP},\n    url = {https://ieeexplore.ieee.org/document/9261115},\n    volume = {23},\n    pages = {4220 - 4231},\n    doi = {10.1109/TMM.2020.3038315},\n    abstract = {Automatic dietary monitoring (ADM) stands as a challenging application in wearable healthcare technologies. In this paper, we define an ADM to perform food intake classification (FIC) over throat microphone recordings. We investigate the use of transfer learning to design an improved FIC system. Although labeled data with acoustic close-talk microphones are abundant, throat data is scarce. Therefore, we propose a new adaptation framework based on teacher/student learning. The teacher network is trained over high-quality acoustic microphone recordings, whereas the student network distills deep feature extraction capacity of the teacher over a parallel dataset. Our approach allows us to transfer the representational capacity, adds robustness to the resulting model, and improves the FIC through throat microphone recordings. The classification problem is formulated as a spectra-temporal sequence recognition using the Convolutional LSTM (ConvLSTM) models. We evaluate the proposed approach using a large scale acoustic dataset collected from online recordings, an in-house food intake throat microphone dataset, and a parallel speech dataset. The bidirectional ConvLSTM network with the proposed domain adaptation approach consistently outperforms the SVM- and CNN-based baseline methods and attains 85.2% accuracy for the classification of 10 different food intake items. This translates to 17.8% accuracy improvement with the proposed domain adaptation.},\n    year = {2021},\n}\n\n
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\n Automatic dietary monitoring (ADM) stands as a challenging application in wearable healthcare technologies. In this paper, we define an ADM to perform food intake classification (FIC) over throat microphone recordings. We investigate the use of transfer learning to design an improved FIC system. Although labeled data with acoustic close-talk microphones are abundant, throat data is scarce. Therefore, we propose a new adaptation framework based on teacher/student learning. The teacher network is trained over high-quality acoustic microphone recordings, whereas the student network distills deep feature extraction capacity of the teacher over a parallel dataset. Our approach allows us to transfer the representational capacity, adds robustness to the resulting model, and improves the FIC through throat microphone recordings. The classification problem is formulated as a spectra-temporal sequence recognition using the Convolutional LSTM (ConvLSTM) models. We evaluate the proposed approach using a large scale acoustic dataset collected from online recordings, an in-house food intake throat microphone dataset, and a parallel speech dataset. The bidirectional ConvLSTM network with the proposed domain adaptation approach consistently outperforms the SVM- and CNN-based baseline methods and attains 85.2% accuracy for the classification of 10 different food intake items. This translates to 17.8% accuracy improvement with the proposed domain adaptation.\n
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\n \n\n \n \n \n \n \n \n Use of affect context in dyadic interactions for continuous emotion recognition.\n \n \n \n \n\n\n \n Fatima, S. N.; and Erzin, E.\n\n\n \n\n\n\n Speech Communication, 132: 70-82. 2021.\n \n\n\n\n
\n\n\n\n \n \n \"UsePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{FATIMA202170,\n    title = {Use of affect context in dyadic interactions for continuous emotion recognition},\n    journal = {Speech Communication},\n    volume = {132},\n    pages = {70-82},\n    year = {2021},\n    issn = {0167-6393},\n    doi = {https://doi.org/10.1016/j.specom.2021.05.010},\n    url = {https://www.sciencedirect.com/science/article/pii/S0167639321000601},\n    author = {Syeda Narjis Fatima and Engin Erzin},\n    keywords = {Dyadic interactions,Continuous emotion recognition (CER),Dyadic affect context (DAC),CNN,ConvLSTM},\n    abstract = {Emotional dependencies play a crucial role in understanding complexities of dyadic interactions. Recent studies have shown that affect recognition tasks can benefit by the incorporation of a particular interaction’s context, however, the investigation of affect context in dyadic settings using neural network frameworks remains a complex and open problem. In this paper, we formulate the concept of dyadic affect context (DAC) and propose convolutional neural network (CNN) based architectures to model and incorporate DAC to improve continuous emotion recognition (CER) in dyadic scenarios. We begin by defining a CNN architecture for single-subject CER-based on speech and body motion data. We then introduce dyadic CER as a two-stage regression framework. Specifically, we propose two dyadic CNN architectures where cross-speaker affect contribution to the CER task is achieved by: (i) the fusion of cross-subject affect (FoA) or (ii) the fusion of cross-subject feature maps (FoM). Based on the preceding dyadic models, we finally propose a new Convolutional LSTM (ConvLSTM) model for the dyadic CER. ConvLSTM architecture captures local spectro-temporal correlations in speech and body motion as well as the long-term affect inter-dependencies between subjects. Our multimodal analysis demonstrates that modeling and incorporation of the DAC in the proposed CER models provide significant performance improvements on the USC CreativeIT database and the achieved results compare favorably to the state-of-the-art.},\n    publisher = {Elsevier B.V.},\n}\n\n
\n
\n\n\n
\n Emotional dependencies play a crucial role in understanding complexities of dyadic interactions. Recent studies have shown that affect recognition tasks can benefit by the incorporation of a particular interaction’s context, however, the investigation of affect context in dyadic settings using neural network frameworks remains a complex and open problem. In this paper, we formulate the concept of dyadic affect context (DAC) and propose convolutional neural network (CNN) based architectures to model and incorporate DAC to improve continuous emotion recognition (CER) in dyadic scenarios. We begin by defining a CNN architecture for single-subject CER-based on speech and body motion data. We then introduce dyadic CER as a two-stage regression framework. Specifically, we propose two dyadic CNN architectures where cross-speaker affect contribution to the CER task is achieved by: (i) the fusion of cross-subject affect (FoA) or (ii) the fusion of cross-subject feature maps (FoM). Based on the preceding dyadic models, we finally propose a new Convolutional LSTM (ConvLSTM) model for the dyadic CER. ConvLSTM architecture captures local spectro-temporal correlations in speech and body motion as well as the long-term affect inter-dependencies between subjects. Our multimodal analysis demonstrates that modeling and incorporation of the DAC in the proposed CER models provide significant performance improvements on the USC CreativeIT database and the achieved results compare favorably to the state-of-the-art.\n
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\n \n\n \n \n \n \n \n \n Engagement Rewarded Actor-Critic with Conservative Q-Learning for Speech-Driven Laughter Backchannel Generation.\n \n \n \n \n\n\n \n Bayramoğlu, Ö. Z.; Erzin, E.; Sezgin, T. M.; and Yemez, Y.\n\n\n \n\n\n\n In Proceedings of the 2021 International Conference on Multimodal Interaction, pages 613–618, New York, NY, USA, 2021. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n \"EngagementPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{10.1145/3462244.3479944,\n    author = {Bayramo\\u{g}lu, \\"{O}yk\\"{u} Zeynep and Erzin, Engin and Sezgin, Tevfik Metin and Yemez, Y\\"{u}cel},\n    title = {Engagement Rewarded Actor-Critic with Conservative Q-Learning for Speech-Driven Laughter Backchannel Generation},\n    year = {2021},\n    isbn = {9781450384810},\n    publisher = {Association for Computing Machinery},\n    address = {New York, NY, USA},\n    url = {https://doi.org/10.1145/3462244.3479944},\n    doi = {10.1145/3462244.3479944},\n    abstract = {We propose a speech-driven laughter backchannel generation model to reward engagement during human-agent interaction. We formulate the problem as a Markov decision process where speech signal represents the state and the objective is to maximize human engagement. Since online training is often impractical in the case of human-agent interaction, we utilize the existing human-to-human dyadic interaction datasets to train our agent for the backchannel generation task. We address the problem using an actor-critic method based on conservative Q-learning (CQL), that mitigates the distributional shift problem by suppressing Q-value over-estimation during training. The proposed CQL based approach is evaluated objectively on the IEMOCAP dataset for laughter generation task. When compared to the existing off-policy Q-learning methods, we observe an improved compliance with the dataset in terms of laugh generation rate. Furthermore, we show the effectiveness of the learned policy by estimating the expected engagement using off-policy policy evaluation techniques.},\n    booktitle = {Proceedings of the 2021 International Conference on Multimodal Interaction},\n    pages = {613–618},\n    keywords = {human-agent interaction,backchannels,offline reinforcement learning,user engagement},\n}\n\n
\n
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\n We propose a speech-driven laughter backchannel generation model to reward engagement during human-agent interaction. We formulate the problem as a Markov decision process where speech signal represents the state and the objective is to maximize human engagement. Since online training is often impractical in the case of human-agent interaction, we utilize the existing human-to-human dyadic interaction datasets to train our agent for the backchannel generation task. We address the problem using an actor-critic method based on conservative Q-learning (CQL), that mitigates the distributional shift problem by suppressing Q-value over-estimation during training. The proposed CQL based approach is evaluated objectively on the IEMOCAP dataset for laughter generation task. When compared to the existing off-policy Q-learning methods, we observe an improved compliance with the dataset in terms of laugh generation rate. Furthermore, we show the effectiveness of the learned policy by estimating the expected engagement using off-policy policy evaluation techniques.\n
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\n \n\n \n \n \n \n \n \n Investigating Contributions of Speech and Facial Landmarks for Talking Head Generation.\n \n \n \n \n\n\n \n Kesim, E.; and Erzin, E.\n\n\n \n\n\n\n In Proc. Interspeech 2021, pages 1624–1628, 2021. \n \n\n\n\n
\n\n\n\n \n \n \"InvestigatingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{kesim21_interspeech,\n    author = {Ege Kesim and Engin Erzin},\n    title = {{Investigating Contributions of Speech and Facial Landmarks for Talking Head Generation}},\n    year = {2021},\n    booktitle = {Proc. Interspeech 2021},\n    pages = {1624--1628},\n    doi = {10.21437/Interspeech.2021-1585},\n    url = {https://www.isca-speech.org/archive/interspeech_2021/kesim21_interspeech.html},\n    abstract = {Talking head generation is an active research problem. It has been widely studied as a direct speech-to-video or two stage speech-to-landmarks-to-video mapping problem. In this study, our main motivation is to assess individual and joint contributions of the speech and facial landmarks to the talking head generation quality through a state-of-the-art generative adversarial network (GAN) architecture. Incorporating frame and sequence discriminators and a feature matching loss, we investigate performances of speech only, landmark only and joint speech and landmark driven talking head generation on the CREMA-D dataset. Objective evaluations using the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) and landmark distance (LMD) indicate that while landmarks bring PSNR and SSIM improvements to the speech driven system, speech brings LMD improvement to the landmark driven system. Furthermore, feature matching is observed to improve the speech driven talking head generation models significantly.},\n}\n\n
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\n Talking head generation is an active research problem. It has been widely studied as a direct speech-to-video or two stage speech-to-landmarks-to-video mapping problem. In this study, our main motivation is to assess individual and joint contributions of the speech and facial landmarks to the talking head generation quality through a state-of-the-art generative adversarial network (GAN) architecture. Incorporating frame and sequence discriminators and a feature matching loss, we investigate performances of speech only, landmark only and joint speech and landmark driven talking head generation on the CREMA-D dataset. Objective evaluations using the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) and landmark distance (LMD) indicate that while landmarks bring PSNR and SSIM improvements to the speech driven system, speech brings LMD improvement to the landmark driven system. Furthermore, feature matching is observed to improve the speech driven talking head generation models significantly.\n
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\n \n\n \n \n \n \n \n Reusetracker: Fast yet accurate multicore reuse distance analyzer.\n \n \n \n\n\n \n Sasongko, M. A.; Chabbi, M.; Marzijarani, M. B.; and Unat, D.\n\n\n \n\n\n\n ACM Transactions on Architecture and Code Optimization (TACO), 19(1): 1–25. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{sasongko2021reusetracker,\n    title = {Reusetracker: Fast yet accurate multicore reuse distance analyzer},\n    author = {Sasongko, Muhammad Aditya and Chabbi, Milind and Marzijarani, Mandana Bagheri and Unat, Didem},\n    journal = {ACM Transactions on Architecture and Code Optimization (TACO)},\n    volume = {19},\n    number = {1},\n    pages = {1--25},\n    year = {2021},\n    publisher = {ACM New York, NY},\n}\n\n
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\n \n\n \n \n \n \n \n End-to-end rate-distortion optimized learned hierarchical bi-directional video compression.\n \n \n \n\n\n \n Yılmaz, M A.; and Tekalp, A M.\n\n\n \n\n\n\n IEEE Transactions on Image Processing, 31: 974–983. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{yilmaz2021end,\n    title = {End-to-end rate-distortion optimized learned hierarchical bi-directional video compression},\n    author = {Y{\\i}lmaz, M Ak{\\i}n and Tekalp, A Murat},\n    journal = {IEEE Transactions on Image Processing},\n    volume = {31},\n    pages = {974--983},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n A Gated Fusion Network for Dynamic Saliency Prediction.\n \n \n \n\n\n \n Kocak, A.; Erdem, E.; and Erdem, A.\n\n\n \n\n\n\n IEEE Transactions on Cognitive and Developmental Systems, 14(3): 995–1008. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{kocak2021gated,\n    title = {A Gated Fusion Network for Dynamic Saliency Prediction},\n    author = {Kocak, Aysun and Erdem, Erkut and Erdem, Aykut},\n    journal = {IEEE Transactions on Cognitive and Developmental Systems},\n    volume = {14},\n    number = {3},\n    pages = {995--1008},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Metaqa: Combining expert agents for multi-skill question answering.\n \n \n \n\n\n \n Puerto, H.; Şahin, G. G.; and Gurevych, I.\n\n\n \n\n\n\n arXiv preprint arXiv:2112.01922. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{puerto2021metaqa,\n    title = {Metaqa: Combining expert agents for multi-skill question answering},\n    author = {Puerto, Haritz and {\\c{S}}ahin, G{\\"o}zde G{\\"u}l and Gurevych, Iryna},\n    journal = {arXiv preprint arXiv:2112.01922},\n    year = {2021},\n}\n\n
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\n \n\n \n \n \n \n \n Burst photography for learning to enhance extremely dark images.\n \n \n \n\n\n \n Karadeniz, A. S.; Erdem, E.; and Erdem, A.\n\n\n \n\n\n\n IEEE Transactions on Image Processing, 30: 9372–9385. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{karadeniz2021burst,\n    title = {Burst photography for learning to enhance extremely dark images},\n    author = {Karadeniz, Ahmet Serdar and Erdem, Erkut and Erdem, Aykut},\n    journal = {IEEE Transactions on Image Processing},\n    volume = {30},\n    pages = {9372--9385},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n From Noon to Sunset: Interactive Rendering, Relighting, and Recolouring of Landscape Photographs by Modifying Solar Position.\n \n \n \n\n\n \n Türe, M.; Çıklabakkal, M. E.; Erdem, A.; Erdem, E.; Satılmış, P.; and Akyüz, A. O.\n\n\n \n\n\n\n In Computer Graphics Forum, volume 40, pages 500–515, 2021. Wiley Online Library\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{ture2021noon,\n    title = {From Noon to Sunset: Interactive Rendering, Relighting, and Recolouring of Landscape Photographs by Modifying Solar Position},\n    author = {T{\\"u}re, Murat and {\\c{C}}{\\i}klabakkal, Mustafa Ege and Erdem, Aykut and Erdem, Erkut and Sat{\\i}lm{\\i}{\\c{s}}, Pinar and Aky{\\"u}z, Ahmet Oguz},\n    booktitle = {Computer Graphics Forum},\n    volume = {40},\n    number = {6},\n    pages = {500--515},\n    year = {2021},\n    organization = {Wiley Online Library},\n}\n\n
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\n \n\n \n \n \n \n \n MSVD-Turkish: a comprehensive multimodal video dataset for integrated vision and language research in Turkish.\n \n \n \n\n\n \n Citamak, B.; Caglayan, O.; Kuyu, M.; Erdem, E.; Erdem, A.; Madhyastha, P.; and Specia, L.\n\n\n \n\n\n\n Machine Translation, 35: 265–288. 2021.\n \n\n\n\n
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@article{citamak2021msvd,\n    title = {MSVD-Turkish: a comprehensive multimodal video dataset for integrated vision and language research in Turkish},\n    author = {Citamak, Begum and Caglayan, Ozan and Kuyu, Menekse and Erdem, Erkut and Erdem, Aykut and Madhyastha, Pranava and Specia, Lucia},\n    journal = {Machine Translation},\n    volume = {35},\n    pages = {265--288},\n    year = {2021},\n    publisher = {Springer},\n}\n\n
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\n \n\n \n \n \n \n \n Synthetic18K: Learning better representations for person re-ID and attribute recognition from 1.4 million synthetic images.\n \n \n \n\n\n \n Uner, O. C.; Aslan, C.; Ercan, B.; Ates, T.; Celikcan, U.; Erdem, A.; and Erdem, E.\n\n\n \n\n\n\n Signal Processing: Image Communication, 97: 116335. 2021.\n \n\n\n\n
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@article{uner2021synthetic18k,\n    title = {Synthetic18K: Learning better representations for person re-ID and attribute recognition from 1.4 million synthetic images},\n    author = {Uner, Onur Can and Aslan, Cem and Ercan, Burak and Ates, Tayfun and Celikcan, Ufuk and Erdem, Aykut and Erdem, Erkut},\n    journal = {Signal Processing: Image Communication},\n    volume = {97},\n    pages = {116335},\n    year = {2021},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n NOVA: Rendering virtual worlds with humans for computer vision tasks.\n \n \n \n\n\n \n Kerim, A.; Aslan, C.; Celikcan, U.; Erdem, E.; and Erdem, A.\n\n\n \n\n\n\n In Computer Graphics Forum, volume 40, pages 258–272, 2021. Wiley Online Library\n \n\n\n\n
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@inproceedings{kerim2021nova,\n    title = {NOVA: Rendering virtual worlds with humans for computer vision tasks},\n    author = {Kerim, Abdulrahman and Aslan, Cem and Celikcan, Ufuk and Erdem, Erkut and Erdem, Aykut},\n    booktitle = {Computer Graphics Forum},\n    volume = {40},\n    number = {6},\n    pages = {258--272},\n    year = {2021},\n    organization = {Wiley Online Library},\n}\n\n
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\n \n\n \n \n \n \n \n Using synthetic data for person tracking under adverse weather conditions.\n \n \n \n\n\n \n Kerim, A.; Celikcan, U.; Erdem, E.; and Erdem, A.\n\n\n \n\n\n\n Image and Vision Computing, 111: 104187. 2021.\n \n\n\n\n
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@article{kerim2021using,\n    title = {Using synthetic data for person tracking under adverse weather conditions},\n    author = {Kerim, Abdulrahman and Celikcan, Ufuk and Erdem, Erkut and Erdem, Aykut},\n    journal = {Image and Vision Computing},\n    volume = {111},\n    pages = {104187},\n    year = {2021},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n Leveraging auxiliary image descriptions for dense video captioning.\n \n \n \n\n\n \n Boran, E.; Erdem, A.; Ikizler-Cinbis, N.; Erdem, E.; Madhyastha, P.; and Specia, L.\n\n\n \n\n\n\n Pattern Recognition Letters, 146: 70–76. 2021.\n \n\n\n\n
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@article{boran2021leveraging,\n    title = {Leveraging auxiliary image descriptions for dense video captioning},\n    author = {Boran, Emre and Erdem, Aykut and Ikizler-Cinbis, Nazli and Erdem, Erkut and Madhyastha, Pranava and Specia, Lucia},\n    journal = {Pattern Recognition Letters},\n    volume = {146},\n    pages = {70--76},\n    year = {2021},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n Adaptive human force scaling via admittance control for physical human-robot interaction.\n \n \n \n\n\n \n Hamad, Y. M; Aydin, Y.; and Basdogan, C.\n\n\n \n\n\n\n IEEE Transactions on Haptics, 14(4): 750–761. 2021.\n \n\n\n\n
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@article{hamad2021adaptive,\n    title = {Adaptive human force scaling via admittance control for physical human-robot interaction},\n    author = {Hamad, Yahya M and Aydin, Yusuf and Basdogan, Cagatay},\n    journal = {IEEE Transactions on Haptics},\n    volume = {14},\n    number = {4},\n    pages = {750--761},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Towards collaborative drilling with a cobot using admittance controller.\n \n \n \n\n\n \n Aydin, Y.; Sirintuna, D.; and Basdogan, C.\n\n\n \n\n\n\n Transactions of the Institute of Measurement and Control, 43(8): 1760–1773. 2021.\n \n\n\n\n
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@article{aydin2021towards,\n    title = {Towards collaborative drilling with a cobot using admittance controller},\n    author = {Aydin, Yusuf and Sirintuna, Doganay and Basdogan, Cagatay},\n    journal = {Transactions of the Institute of Measurement and Control},\n    volume = {43},\n    number = {8},\n    pages = {1760--1773},\n    year = {2021},\n    publisher = {SAGE Publications Sage UK: London, England},\n}\n\n
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\n \n\n \n \n \n \n \n Use of affect context in dyadic interactions for continuous emotion recognition.\n \n \n \n\n\n \n Fatima, S. N.; and Erzin, E.\n\n\n \n\n\n\n Speech Communication, 132: 70–82. 2021.\n \n\n\n\n
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@article{fatima2021use,\n    title = {Use of affect context in dyadic interactions for continuous emotion recognition},\n    author = {Fatima, Syeda Narjis and Erzin, Engin},\n    journal = {Speech Communication},\n    volume = {132},\n    pages = {70--82},\n    year = {2021},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n Polytopic matrix factorization: Determinant maximization based criterion and identifiability.\n \n \n \n\n\n \n Tatli, G.; and Erdogan, A. T\n\n\n \n\n\n\n IEEE Transactions on Signal Processing, 69: 5431–5447. 2021.\n \n\n\n\n
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@article{tatli2021polytopic,\n    title = {Polytopic matrix factorization: Determinant maximization based criterion and identifiability},\n    author = {Tatli, Gokcan and Erdogan, Alper T},\n    journal = {IEEE Transactions on Signal Processing},\n    volume = {69},\n    pages = {5431--5447},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression.\n \n \n \n\n\n \n Tekalp, A M.; Covell, M.; Timofte, R.; and Dong, C.\n\n\n \n\n\n\n IEEE Journal of Selected Topics in Signal Processing, 15(2): 157–161. 2021.\n \n\n\n\n
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@article{tekalp2021introduction,\n    title = {Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression},\n    author = {Tekalp, A Murat and Covell, Michele and Timofte, Radu and Dong, Chao},\n    journal = {IEEE Journal of Selected Topics in Signal Processing},\n    volume = {15},\n    number = {2},\n    pages = {157--161},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n The Universal Fog Proxy: A Third-party Authentication Solution for Federated Fog Systems with Multiple Protocols.\n \n \n \n\n\n \n Ali, A.; Şahin, A. U.; Özkasap, Ö.; and Lin, Y.\n\n\n \n\n\n\n IEEE Network, 35(6): 285–291. 2021.\n \n\n\n\n
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@article{ali2021universal,\n    title = {The Universal Fog Proxy: A Third-party Authentication Solution for Federated Fog Systems with Multiple Protocols},\n    author = {Ali, Asad and {\\c{S}}ahin, Ali Utkan and {\\"O}zkasap, {\\"O}znur and Lin, Ying-Dar},\n    journal = {IEEE Network},\n    volume = {35},\n    number = {6},\n    pages = {285--291},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Interlaced: Fully decentralized churn stabilization for skip graph-based dhts.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n Journal of Parallel and Distributed Computing, 149: 13–28. 2021.\n \n\n\n\n
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@article{hassanzadeh2021interlaced,\n    title = {Interlaced: Fully decentralized churn stabilization for skip graph-based dhts},\n    author = {Hassanzadeh-Nazarabadi, Yahya and K{\\"u}p{\\c{c}}{\\"u}, Alptekin and {\\"O}zkasap, {\\"O}znur},\n    journal = {Journal of Parallel and Distributed Computing},\n    volume = {149},\n    pages = {13--28},\n    year = {2021},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n Lightchain: Scalable dht-based blockchain.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n IEEE Transactions on Parallel and Distributed Systems, 32(10): 2582–2593. 2021.\n \n\n\n\n
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@article{hassanzadeh2021lightchain,\n    title = {Lightchain: Scalable dht-based blockchain},\n    author = {Hassanzadeh-Nazarabadi, Yahya and K{\\"u}p{\\c{c}}{\\"u}, Alptekin and {\\"O}zkasap, {\\"O}znur},\n    journal = {IEEE Transactions on Parallel and Distributed Systems},\n    volume = {32},\n    number = {10},\n    pages = {2582--2593},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n A computational-graph partitioning method for training memory-constrained DNNs.\n \n \n \n\n\n \n Qararyah, F.; Wahib, M.; Dikbayır, D.; Belviranli, M. E.; and Unat, D.\n\n\n \n\n\n\n Parallel computing, 104: 102792. 2021.\n \n\n\n\n
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@article{qararyah2021computational,\n    title = {A computational-graph partitioning method for training memory-constrained DNNs},\n    author = {Qararyah, Fareed and Wahib, Mohamed and Dikbay{\\i}r, Do{\\u{g}}a and Belviranli, Mehmet Esat and Unat, Didem},\n    journal = {Parallel computing},\n    volume = {104},\n    pages = {102792},\n    year = {2021},\n    publisher = {Elsevier},\n}\n\n
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\n \n\n \n \n \n \n \n A split execution model for SpTRSV.\n \n \n \n\n\n \n Ahmad, N.; Yilmaz, B.; and Unat, D.\n\n\n \n\n\n\n IEEE Transactions on Parallel and Distributed Systems, 32(11): 2809–2822. 2021.\n \n\n\n\n
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@article{ahmad2021split,\n    title = {A split execution model for SpTRSV},\n    author = {Ahmad, Najeeb and Yilmaz, Buse and Unat, Didem},\n    journal = {IEEE Transactions on Parallel and Distributed Systems},\n    volume = {32},\n    number = {11},\n    pages = {2809--2822},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Normal mode analysis of KRas4B reveals partner specific dynamics.\n \n \n \n\n\n \n Eren, M.; Tuncbag, N.; Jang, H.; Nussinov, R.; Gursoy, A.; and Keskin, O.\n\n\n \n\n\n\n The Journal of Physical Chemistry B, 125(20): 5210–5221. 2021.\n \n\n\n\n
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@article{eren2021normal,\n    title = {Normal mode analysis of KRas4B reveals partner specific dynamics},\n    author = {Eren, Meryem and Tuncbag, Nurcan and Jang, Hyunbum and Nussinov, Ruth and Gursoy, Attila and Keskin, Ozlem},\n    journal = {The Journal of Physical Chemistry B},\n    volume = {125},\n    number = {20},\n    pages = {5210--5221},\n    year = {2021},\n    publisher = {ACS Publications},\n}\n\n
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\n \n\n \n \n \n \n \n Mechanistic Differences of Activation of Rac1P29S and Rac1A159V.\n \n \n \n\n\n \n Senyuz, S.; Jang, H.; Nussinov, R.; Keskin, O.; and Gursoy, A.\n\n\n \n\n\n\n The Journal of Physical Chemistry B, 125(15): 3790–3802. 2021.\n \n\n\n\n
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@article{senyuz2021mechanistic,\n    title = {Mechanistic Differences of Activation of Rac1P29S and Rac1A159V},\n    author = {Senyuz, Simge and Jang, Hyunbum and Nussinov, Ruth and Keskin, Ozlem and Gursoy, Attila},\n    journal = {The Journal of Physical Chemistry B},\n    volume = {125},\n    number = {15},\n    pages = {3790--3802},\n    year = {2021},\n    publisher = {ACS Publications},\n}\n\n
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\n \n\n \n \n \n \n \n Slamp: Stochastic latent appearance and motion prediction.\n \n \n \n\n\n \n Akan, A. K.; Erdem, E.; Erdem, A.; and Güney, F.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 14728–14737, 2021. \n \n\n\n\n
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@inproceedings{akan2021slamp,\n    title = {Slamp: Stochastic latent appearance and motion prediction},\n    author = {Akan, Adil Kaan and Erdem, Erkut and Erdem, Aykut and G{\\"u}ney, Fatma},\n    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision},\n    pages = {14728--14737},\n    year = {2021},\n}\n\n
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\n \n\n \n \n \n \n \n Cross-lingual visual pre-training for multimodal machine translation.\n \n \n \n\n\n \n Caglayan, O.; Kuyu, M.; Amac, M. S.; Madhyastha, P.; Erdem, E.; Erdem, A.; and Specia, L.\n\n\n \n\n\n\n arXiv preprint arXiv:2101.10044. 2021.\n \n\n\n\n
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@article{caglayan2021cross,\n    title = {Cross-lingual visual pre-training for multimodal machine translation},\n    author = {Caglayan, Ozan and Kuyu, Menekse and Amac, Mustafa Sercan and Madhyastha, Pranava and Erdem, Erkut and Erdem, Aykut and Specia, Lucia},\n    journal = {arXiv preprint arXiv:2101.10044},\n    year = {2021},\n}\n\n
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\n \n\n \n \n \n \n \n Leveraging frequency based salient spatial sound localization to improve 360 video saliency prediction.\n \n \n \n\n\n \n Cokelek, M.; Imamoglu, N.; Ozcinar, C.; Erdem, E.; and Erdem, A.\n\n\n \n\n\n\n In 2021 17th International Conference on Machine Vision and Applications (MVA), pages 1–5, 2021. IEEE\n \n\n\n\n
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@inproceedings{cokelek2021leveraging,\n    title = {Leveraging frequency based salient spatial sound localization to improve 360 video saliency prediction},\n    author = {Cokelek, Mert and Imamoglu, Nevrez and Ozcinar, Cagri and Erdem, Erkut and Erdem, Aykut},\n    booktitle = {2021 17th International Conference on Machine Vision and Applications (MVA)},\n    pages = {1--5},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@inproceedings{safadoust2021self,\n    title = {Self-supervised monocular scene decomposition and depth estimation},\n    author = {Safadoust, Sadra and G{\\"u}ney, Fatma},\n    booktitle = {2021 International Conference on 3D Vision (3DV)},\n    pages = {627--636},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Locally Rigid Registration for Structural Deformation Monitoring.\n \n \n \n\n\n \n Korkmaz, C.; Köprücü, N.; Açıkgöz, S.; and Güney, F.\n\n\n \n\n\n\n Montreal Robotics. 2021.\n \n\n\n\n
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@article{korkmazlocally,\n    title = {Locally Rigid Registration for Structural Deformation Monitoring},\n    author = {Korkmaz, Caner and K{\\"o}pr{\\"u}c{\\"u}, Nursena and A{\\c{c}}{\\i}kg{\\"o}z, Sinan and G{\\"u}ney, Fatma},\n    year = {2021},\n    journal = {Montreal Robotics},\n}\n\n
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\n \n\n \n \n \n \n \n Engagement rewarded actor-critic with conservative Q-learning for speech-driven laughter backchannel generation.\n \n \n \n\n\n \n Bayramoğlu, Ö. Z.; Erzin, E.; Sezgin, T. M.; and Yemez, Y.\n\n\n \n\n\n\n In Proceedings of the 2021 International Conference on Multimodal Interaction, pages 613–618, 2021. \n \n\n\n\n
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@inproceedings{bayramouglu2021engagement,\n    title = {Engagement rewarded actor-critic with conservative Q-learning for speech-driven laughter backchannel generation},\n    author = {Bayramo{\\u{g}}lu, {\\"O}yk{\\"u} Zeynep and Erzin, Engin and Sezgin, Tevfik Metin and Yemez, Y{\\"u}cel},\n    booktitle = {Proceedings of the 2021 International Conference on Multimodal Interaction},\n    pages = {613--618},\n    year = {2021},\n}\n\n
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\n \n\n \n \n \n \n \n Investigating Contributions of Speech and Facial Landmarks for Talking Head Generation.\n \n \n \n\n\n \n Kesim, E.; and Erzin, E.\n\n\n \n\n\n\n In Interspeech, pages 1624–1628, 2021. \n \n\n\n\n
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@inproceedings{kesim2021investigating,\n    title = {Investigating Contributions of Speech and Facial Landmarks for Talking Head Generation.},\n    author = {Kesim, Ege and Erzin, Engin},\n    booktitle = {Interspeech},\n    pages = {1624--1628},\n    year = {2021},\n}\n\n
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@inproceedings{tatli2021generalized,\n    title = {Generalized polytopic matrix factorization},\n    author = {Tatli, Gokcan and Erdogan, Alper T},\n    booktitle = {ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    pages = {3235--3239},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@inproceedings{kelecs2021computation,\n    title = {On the Computation of PSNR for a Set of Images or Video},\n    author = {Kele{\\c{s}}, Onur and Y$\\iota$lmaz, M Ak$\\iota$n and Tekalp, A Murat and Korkmaz, Cansu and Do{\\u{g}}an, Zafer},\n    booktitle = {2021 Picture Coding Symposium (PCS)},\n    pages = {1--5},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@inproceedings{kirmemis2021practical,\n    title = {A Practical Approach for Rate-Distortion-Perception Analysis in Learned Image Compression},\n    author = {Kirmemis, Ogun and Tekalp, A Murat},\n    booktitle = {2021 Picture Coding Symposium (PCS)},\n    pages = {1--5},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@inproceedings{yilmaz2021self,\n    title = {Self-organized variational autoencoders (self-vae) for learned image compression},\n    author = {Y{\\'\\i}lmaz, M Ak{\\'\\i}n and Keles{\\c{s}}, Onur and G{\\"u}ven, Hilal and Tekalp, A Murat and Malik, Junaid and K{\\'\\i}ranyaz, Serkan},\n    booktitle = {2021 IEEE International Conference on Image Processing (ICIP)},\n    pages = {3732--3736},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@inproceedings{kelecs2021self,\n    title = {Self-organized residual blocks for image super-resolution},\n    author = {Kele{\\c{s}}, Onur and Tekalp, A Murat and Malik, Junaid and K$\\iota$ranyaz, Serkan},\n    booktitle = {2021 IEEE International Conference on Image Processing (ICIP)},\n    pages = {589--593},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@inproceedings{yilmaz2021dfpn,\n    title = {Dfpn: Deformable frame prediction network},\n    author = {Y{\\i}lmaz, M Ak{\\i}n and Tekalp, A Murat},\n    booktitle = {2021 IEEE International Conference on Image Processing (ICIP)},\n    pages = {1944--1948},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@article{akin2021dfpn,\n    title = {DFPN: Deformable Frame Prediction Network},\n    author = {Ak{\\i}n Y{\\i}lmaz, M and Murat Tekalp, A},\n    journal = {arXiv e-prints},\n    pages = {arXiv--2105},\n    year = {2021},\n}\n\n
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@inproceedings{korkmaz2021two,\n    title = {Two-stage domain adapted training for better generalization in real-world image restoration and super-resolution},\n    author = {Korkmaz, Cansu and Tekalp, A Murat and Do{\\u{g}}an, Zafer},\n    booktitle = {2021 IEEE International Conference on Image Processing (ICIP)},\n    pages = {569--573},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@article{erdogan2021zelig,\n    title = {-Zelig: Customizable Blockchain Simulator},\n    author = {Erdogan, Ege and Aydin, Can Arda and Ozkasap, Oznur and Gill, Waris},\n    journal = {arXiv preprint arXiv:2107.07972},\n    year = {2021},\n}\n\n
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@inproceedings{hassanzadeh2021smart,\n    title = {Smart Contract-enabled LightChain Test Network},\n    author = {Hassanzadeh-Nazarabadi, Yahya and Kshatriya, Kedar and {\\"O}zkasap, {\\"O}znur},\n    booktitle = {IEEE INFOCOM 2021-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)},\n    pages = {1--2},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@article{tumen2021segmentation,\n    title = {Segmentation and Recognition of Offline Sketch Scenes Using Dynamic Programming},\n    author = {T{\\"u}men, Recep Sinan and Sezgin, Metin},\n    journal = {IEEE Computer Graphics and Applications},\n    volume = {42},\n    number = {1},\n    pages = {56--72},\n    year = {2021},\n    publisher = {IEEE},\n}\n\n
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@inproceedings{yesilbek2021training,\n    title = {On training sketch recognizers for new domains},\n    author = {Yesilbek, Kemal Tugrul and Sezgin, Metin},\n    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},\n    pages = {2142--2149},\n    year = {2021},\n}\n\n
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\n \n\n \n \n \n \n \n ATM Allocation Using Decision Tree-Based Algorithms.\n \n \n \n\n\n \n Yurdakul, H. H.; Kaşıkcı, K.; Cağatay, İ.; Güven, M.; Koraş, M.; Akgün, B.; and Gönen, M.\n\n\n \n\n\n\n In 2021 29th Signal Processing and Communications Applications Conference (SIU), pages 1–4, 2021. IEEE\n \n\n\n\n
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@inproceedings{yurdakul2021atm,\n    title = {ATM Allocation Using Decision Tree-Based Algorithms},\n    author = {Yurdakul, Hazal Hasret and Ka{\\c{s}}{\\i}kc{\\i}, Kerem and Ca{\\u{g}}atay, {\\.I}lhan and G{\\"u}ven, Melih and Kora{\\c{s}}, Murat and Akg{\\"u}n, Bar{\\i}{\\c{s}} and G{\\"o}nen, Mehmet},\n    booktitle = {2021 29th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2021},\n    organization = {IEEE},\n}\n\n
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@inproceedings{unat2021comscribe,\n    title = {ComScribe: Identifying Intra-node GPU Communication},\n    author = {Unat, Didem},\n    booktitle = {Benchmarking, Measuring, and Optimizing: Third BenchCouncil International Symposium, Bench 2020, Virtual Event, November 15--16, 2020, Revised Selected Papers},\n    volume = {12614},\n    pages = {157},\n    year = {2021},\n    organization = {Springer Nature},\n}\n\n
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@article{nussinov2021inhibition,\n    title = {Inhibition of nonfunctional Ras},\n    author = {Nussinov, Ruth and Jang, Hyunbum and Gursoy, Attila and Keskin, Ozlem and Gaponenko, Vadim},\n    journal = {Cell chemical biology},\n    volume = {28},\n    number = {2},\n    pages = {121--133},\n    year = {2021},\n    publisher = {Elsevier},\n}\n\n
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@article{8811590,\n    author = {Kirmizioglu, Riza Arda and Tekalp, A. Murat},\n    journal = {IEEE Transactions on Multimedia},\n    title = {Multi-Party WebRTC Services Using Delay and Bandwidth Aware SDN-Assisted IP Multicasting of Scalable Video Over 5G Networks},\n    year = {2020},\n    volume = {22},\n    number = {4},\n    pages = {1005-1015},\n    doi = {10.1109/TMM.2019.2937170}}
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@article{8960478,\n    author = {Ozdamar, Idil and Alipour, M. Reza and Delhaye, Benoit P. and Lefèvre, Philippe and Basdogan, Cagatay},\n    journal = {IEEE Transactions on Haptics},\n    title = {Step-Change in Friction Under Electrovibration},\n    year = {2020},\n    volume = {13},\n    number = {1},\n    pages = {137-143},\n    doi = {10.1109/TOH.2020.2966992}}
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@inproceedings{9169426,\n    author = {Hassanzadeh-Nazarabadi, Yahya and {\\c{S}}ahin, Ali Utkan and {\\"O}zkasap, {\\"O}znur and K{\\"u}p{\\c{c}}{\\"u}, Alptekin},\n    booktitle = {2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)},\n    title = {SkipSim: Scalable Skip Graph Simulator},\n    year = {2020},\n    doi = {10.1109/ICBC48266.2020.9169426}}
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\n \n\n \n \n \n \n \n A containerized proof-of-concept implementation of LightChain system.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Nayal, N.; Hamdan, S. S.; Özkasap, Ö.; and Küpçü, A.\n\n\n \n\n\n\n In 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2020. \n \n\n\n\n
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@inproceedings{9169463,\n    author = {Hassanzadeh-Nazarabadi, Yahya and Nayal, Nazir and Hamdan, Shadi Sameh and {\\"O}zkasap, {\\"O}znur and K{\\"u}p{\\c{c}}{\\"u}, Alptekin},\n    booktitle = {2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)},\n    title = {A containerized proof-of-concept implementation of LightChain system},\n    year = {2020},\n    doi = {10.1109/ICBC48266.2020.9169463}}
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\n \n\n \n \n \n \n \n Shrinkage as Activation for Learned Image Compression.\n \n \n \n\n\n \n Kirmemis, O.; and Tekalp, A. M.\n\n\n \n\n\n\n In 2020 IEEE International Conference on Image Processing (ICIP), pages 1301-1305, 2020. \n \n\n\n\n
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@inproceedings{9190974,\n    author = {Kirmemis, Ogun and Tekalp, A. Murat},\n    booktitle = {2020 IEEE International Conference on Image Processing (ICIP)},\n    title = {Shrinkage as Activation for Learned Image Compression},\n    year = {2020},\n    pages = {1301-1305},\n    doi = {10.1109/ICIP40778.2020.9190974}}
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\n \n\n \n \n \n \n \n Belief Regulated Dual Propagation Nets for Learning Action Effects on Groups of Articulated Objects.\n \n \n \n\n\n \n Tekden, A. E.; Erdem, A.; Erdem, E.; Imre, M.; Seker, M. Y.; and Ugur, E.\n\n\n \n\n\n\n In 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020. \n \n\n\n\n
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@inproceedings{9196878,\n    author = {Tekden, Ahmet E. and Erdem, Aykut and Erdem, Erkut and Imre, Mert and Seker, M. Yunus and Ugur, Emre},\n    booktitle = {2020 IEEE International Conference on Robotics and Automation (ICRA)},\n    title = {Belief Regulated Dual Propagation Nets for Learning Action Effects on Groups of Articulated Objects},\n    year = {2020},\n    doi = {10.1109/ICRA40945.2020.9196878}}
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@inproceedings{9219605,\n    author = {Assefa, Beakal Gizachew and {\\"O}zkasap, {\\"O}znur and Kizil, Ipek and Aloqaily, Moayad and Bouachir, Ouns},\n    booktitle = {2020 IEEE Symposium on Computers and Communications (ISCC)},\n    title = {Energy Efficiency in SDDC: Considering Server and Network Utilities},\n    year = {2020},\n    doi = {10.1109/ISCC50000.2020.9219605}}
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\n \n\n \n \n \n \n \n EdgeKV: Distributed Key-Value Store for the Network Edge.\n \n \n \n\n\n \n Sonbol, K.; Özkasap, Ö.; Al Oqily, I.; and Aloqaily, M.\n\n\n \n\n\n\n In 2020 IEEE Symposium on Computers and Communications (ISCC), 2020. \n \n\n\n\n
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@inproceedings{9219667,\n    author = {Sonbol, Karim and {\\"O}zkasap, {\\"O}znur and Al Oqily, Ibrahim and Aloqaily, Moayad},\n    booktitle = {2020 IEEE Symposium on Computers and Communications (ISCC)},\n    title = {EdgeKV: Distributed Key-Value Store for the Network Edge},\n    year = {2020},\n    doi = {10.1109/ISCC50000.2020.9219667}}
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\n \n\n \n \n \n \n \n Detecting Human Motion Intention during pHRI Using Artificial Neural Networks Trained by EMG Signals.\n \n \n \n\n\n \n Sirintuna, D.; Ozdamar, I.; Aydin, Y.; and Basdogan, C.\n\n\n \n\n\n\n In 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2020. \n \n\n\n\n
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@inproceedings{9223438,\n    author = {Sirintuna, Doganay and Ozdamar, Idil and Aydin, Yusuf and Basdogan, Cagatay},\n    booktitle = {2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},\n    title = {Detecting Human Motion Intention during pHRI Using Artificial Neural Networks Trained by EMG Signals},\n    year = {2020},\n    doi = {10.1109/RO-MAN47096.2020.9223438}}
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\n \n\n \n \n \n \n \n Chain FL: Decentralized Federated Machine Learning via Blockchain.\n \n \n \n\n\n \n Korkmaz, C.; Kocas, H. E.; Uysal, A.; Masry, A.; Ozkasap, O.; and Akgun, B.\n\n\n \n\n\n\n In 2020 Second International Conference on Blockchain Computing and Applications (BCCA), pages 140-146, 2020. \n \n\n\n\n
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@inproceedings{9274451,\n    author = {Korkmaz, Caner and Kocas, Halil Eralp and Uysal, Ahmet and Masry, Ahmed and Ozkasap, Oznur and Akgun, Baris},\n    booktitle = {2020 Second International Conference on Blockchain Computing and Applications (BCCA)},\n    title = {Chain FL: Decentralized Federated Machine Learning via Blockchain},\n    year = {2020},\n    pages = {140-146},\n    doi = {10.1109/BCCA50787.2020.9274451}}
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\n \n\n \n \n \n \n \n Video Frame Prediction via Deep Learning.\n \n \n \n\n\n \n Yilmaz, M. A.; and Tekalp, A. M.\n\n\n \n\n\n\n In 2020 28th Signal Processing and Communications Applications Conference (SIU), pages 1-4, 2020. \n \n\n\n\n
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@inproceedings{9302047,\n    author = {Yilmaz, M. Akin and Tekalp, A. Murat},\n    booktitle = {2020 28th Signal Processing and Communications Applications Conference (SIU)},\n    title = {Video Frame Prediction via Deep Learning},\n    year = {2020},\n    pages = {1-4},\n    doi = {10.1109/SIU49456.2020.9302047}}
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@inproceedings{9302149,\n    author = {Gill, Waris and {\\"O}zkasap, {\\"O}znur and Gursoy, Attila},\n    booktitle = {2020 28th Signal Processing and Communications Applications Conference (SIU)},\n    title = {Intelligent Edge Computing: State-of-the-art Techniques and Applications},\n    year = {2020},\n    pages = {1-4},\n    doi = {10.1109/SIU49456.2020.9302149}}
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\n \n\n \n \n \n \n \n Multi-Party Videoconferencing Service over Edge-Cloud Based Access Network Infrastructure.\n \n \n \n\n\n \n Kırmızıoğlu, R. A.; Tekalp, A. M.; and Görkemli, B.\n\n\n \n\n\n\n In 2020 28th Signal Processing and Communications Applications Conference (SIU), pages 1-4, 2020. \n \n\n\n\n
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@inproceedings{9302254,\n    author = {K{\\i}rm{\\i}z{\\i}o{\\u{g}}lu, R. Arda and Tekalp, A. Murat and G{\\"o}rkemli, Burak},\n    booktitle = {2020 28th Signal Processing and Communications Applications Conference (SIU)},\n    title = {Multi-Party Videoconferencing Service over Edge-Cloud Based Access Network Infrastructure},\n    year = {2020},\n    pages = {1-4},\n    doi = {10.1109/SIU49456.2020.9302254}}
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\n \n\n \n \n \n \n \n New Results in End-to-end Image and Video Compression by Deep Learning.\n \n \n \n\n\n \n Özsoy, G.; Yılmaz, M.; Kırmemiş, O.; and Tekalp, A. M.\n\n\n \n\n\n\n In 2020 28th Signal Processing and Communications Applications Conference (SIU), pages 1-4, 2020. \n \n\n\n\n
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@inproceedings{9302478,\n    author = {{\\"O}zsoy, G{\\"o}kberk and Y{\\i}lmaz, Melih and K{\\i}rmemi{\\c{s}}, Og{\\"u}n and Tekalp, A. Murat},\n    booktitle = {2020 28th Signal Processing and Communications Applications Conference (SIU)},\n    title = {New Results in End-to-end Image and Video Compression by Deep Learning},\n    year = {2020},\n    pages = {1-4},\n    doi = {10.1109/SIU49456.2020.9302478}}
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@article{Janai2020ComputerVF,\n    title = {Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art},\n    author = {Joel Janai and Fatma G{\\"u}ney and A. Behl and Andreas Geiger},\n    journal = {Found. Trends Comput. Graph. Vis.},\n    year = {2020},\n    volume = {12},\n    pages = {1-308},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n HMI-PRED: A Web Server for Structural Prediction of Host-Microbe Interactions Based on Interface Mimicry.\n \n \n \n\n\n \n Guven-Maiorov, E.; Hakouz, A.; Valjevac, S.; Keskin, O.; Tsai, C.; Gursoy, A.; and Nussinov, R.\n\n\n \n\n\n\n Journal of molecular biology. 2020.\n \n\n\n\n
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@article{GuvenMaiorov2020HMIPREDAW,\n    title = {HMI-PRED: A Web Server for Structural Prediction of Host-Microbe Interactions Based on Interface Mimicry.},\n    author = {Emine Guven-Maiorov and Asma Hakouz and Sukejna Valjevac and O. Keskin and Chung-Jung Tsai and A. Gursoy and R. Nussinov},\n    journal = {Journal of molecular biology},\n    year = {2020},\n    keywords = {CBM},\n}\n\n
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\n \n\n \n \n \n \n \n Oncogenic K-Ras4B Dimerization Enhances Downstream Mitogen-activated Protein Kinase Signaling.\n \n \n \n\n\n \n Muratcioğlu, S.; Aydin, C.; Odabasi, E.; Ozdemir, E.; Firat-Karalar, E. N.; Jang, H.; Tsai, C.; Nussinov, R.; Kavakli, I.; Gursoy, A.; and Keskin, O.\n\n\n \n\n\n\n Journal of Molecular Biology, 432: 1199-1215. 2020.\n \n\n\n\n
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@article{Muratciolu2020OncogenicKD,\n    title = {Oncogenic K-Ras4B Dimerization Enhances Downstream Mitogen-activated Protein Kinase Signaling.},\n    author = {Serena Muratcio{\\u{g}}lu and Cihan Aydin and Ezgi Odabasi and E. Ozdemir and E. N. Firat-Karalar and H. Jang and Chung-Jung Tsai and R. Nussinov and I. Kavakli and A. Gursoy and O. Keskin},\n    journal = {Journal of Molecular Biology},\n    year = {2020},\n    volume = {432},\n    pages = {1199-1215},\n    keywords = {CBM},\n}\n\n
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\n \n\n \n \n \n \n \n Embedding Alternative Conformations of Proteins in Protein-Protein Interaction Networks.\n \n \n \n\n\n \n Halakou, F.; Gürsoy, A.; and Keskin, O.\n\n\n \n\n\n\n Methods in molecular biology, 2074. 2020.\n \n\n\n\n
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@article{Halakou2020EmbeddingAC,\n    title = {Embedding Alternative Conformations of Proteins in Protein-Protein Interaction Networks},\n    author = {Farideh Halakou and Attila G{\\"u}rsoy and O. Keskin},\n    journal = {Methods in molecular biology},\n    year = {2020},\n    volume = {2074},\n    keywords = {CBM},\n}\n\n
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\n \n\n \n \n \n \n \n End-to-End Rate-Distortion Optimization for Bi-Directional Learned Video Compression.\n \n \n \n\n\n \n Yilmaz, M.; and Tekalp, A.\n\n\n \n\n\n\n 2020 IEEE International Conference on Image Processing (ICIP),1311-1315. 2020.\n \n\n\n\n
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@article{Yilmaz2020EndtoEndRO,\n    title = {End-to-End Rate-Distortion Optimization for Bi-Directional Learned Video Compression},\n    author = {M. Yilmaz and A. Tekalp},\n    journal = {2020 IEEE International Conference on Image Processing (ICIP)},\n    year = {2020},\n    pages = {1311-1315},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n A Prediction Framework for Fast Sparse Triangular Solves.\n \n \n \n\n\n \n Ahmad, N.; Yilmaz, B.; and Unat, D.\n\n\n \n\n\n\n In Euro-Par, 2020. \n \n\n\n\n
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@inproceedings{Ahmad2020APF,\n    title = {A Prediction Framework for Fast Sparse Triangular Solves},\n    author = {Najeeb Ahmad and Buse Yilmaz and D. Unat},\n    booktitle = {Euro-Par},\n    year = {2020},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n RESDN: A Novel Metric and Method for Energy Efficient Routing in Software Defined Networks.\n \n \n \n\n\n \n Assefa, B. G.; and Özkasap, Ö.\n\n\n \n\n\n\n IEEE Transactions on Network and Service Management, 17: 736-749. 2020.\n \n\n\n\n
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@article{Assefa2020RESDNAN,\n    title = {RESDN: A Novel Metric and Method for Energy Efficient Routing in Software Defined Networks},\n    author = {Beakal Gizachew Assefa and {\\"O}znur {\\"O}zkasap},\n    journal = {IEEE Transactions on Network and Service Management},\n    year = {2020},\n    volume = {17},\n    pages = {736-749},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Cyberphysical Blockchain-Enabled Peer-to-Peer Energy Trading.\n \n \n \n\n\n \n Ali, F.; Aloqaily, M.; Alfandi, O.; and Ozkasap, O.\n\n\n \n\n\n\n Computer, 53: 56-65. 2020.\n \n\n\n\n
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@article{Ali2020CyberphysicalBP,\n    title = {Cyberphysical Blockchain-Enabled Peer-to-Peer Energy Trading},\n    author = {Faizan Ali and M. Aloqaily and O. Alfandi and O. Ozkasap},\n    journal = {Computer},\n    year = {2020},\n    volume = {53},\n    pages = {56-65},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Adaptive Level Binning: A New Algorithm for Solving Sparse Triangular Systems.\n \n \n \n\n\n \n Yilmaz, B.; Sipahiogrlu, B.; Ahmad, N.; and Unat, D.\n\n\n \n\n\n\n Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region. 2020.\n \n\n\n\n
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@article{Yilmaz2020AdaptiveLB,\n    title = {Adaptive Level Binning: A New Algorithm for Solving Sparse Triangular Systems},\n    author = {Buse Yilmaz and Bugrra Sipahiogrlu and Najeeb Ahmad and D. Unat},\n    journal = {Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region},\n    year = {2020},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Decentralized Utility- and Locality-Aware Replication for Heterogeneous DHT-Based P2P Cloud Storage Systems.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n IEEE Transactions on Parallel and Distributed Systems, 31: 1183-1193. 2020.\n \n\n\n\n
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@article{HassanzadehNazarabadi2020DecentralizedUA,\n    title = {Decentralized Utility- and Locality-Aware Replication for Heterogeneous DHT-Based P2P Cloud Storage Systems},\n    author = {Yahya Hassanzadeh-Nazarabadi and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    journal = {IEEE Transactions on Parallel and Distributed Systems},\n    year = {2020},\n    volume = {31},\n    pages = {1183-1193},\n    keywords = {SAI},\n}\n\n
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\n\n\n\n \n \n \"AffectON:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{bucinca2020affecton,\n    author = {Zana Bucinca and Yucel Yemez and Engin Erzin and Metin Sezgin},\n    title = {AffectON: Incorporating Affect Into Dialog Generation},\n    year = {2020},\n    keywords = {MSP},\n    url = {https://ieeexplore.ieee.org/document/9286511},\n    doi = {10.1109/TAFFC.2020.3043067},\n    abstract = {Due to its expressivity, natural language is paramount for explicit and implicit affective state communication among humans. The same linguistic inquiry (e.g. How are you ?) might induce responses with different affects depending on the affective state of the conversational partner(s) and the context of the conversation. Yet, most dialog systems do not consider affect as constitutive aspect of response generation. In this paper, we introduce AffectON, an approach for generating affective responses during inference. For generating language in a targeted affect, our approach leverages a probabilistic language model and an affective space. AffectON is language model agnostic, since it can work with probabilities generated by any language model (e.g., sequence-to-sequence models, neural language models, n-grams). Hence, it can be employed for both affective dialog and affective language generation. We experimented with affective dialog generation and evaluated the generated text objectively and subjectively. For the subjective part of the evaluation, we designed a custom user interface for rating and provided recommendations for the design of such interfaces. The results, both subjective and objective demonstrate that our approach is successful in pulling the generated language toward the targeted affect, with little sacrifice in syntactic coherence.},\n}\n\n
\n
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\n Due to its expressivity, natural language is paramount for explicit and implicit affective state communication among humans. The same linguistic inquiry (e.g. How are you ?) might induce responses with different affects depending on the affective state of the conversational partner(s) and the context of the conversation. Yet, most dialog systems do not consider affect as constitutive aspect of response generation. In this paper, we introduce AffectON, an approach for generating affective responses during inference. For generating language in a targeted affect, our approach leverages a probabilistic language model and an affective space. AffectON is language model agnostic, since it can work with probabilities generated by any language model (e.g., sequence-to-sequence models, neural language models, n-grams). Hence, it can be employed for both affective dialog and affective language generation. We experimented with affective dialog generation and evaluated the generated text objectively and subjectively. For the subjective part of the evaluation, we designed a custom user interface for rating and provided recommendations for the design of such interfaces. The results, both subjective and objective demonstrate that our approach is successful in pulling the generated language toward the targeted affect, with little sacrifice in syntactic coherence.\n
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\n \n\n \n \n \n \n \n KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media.\n \n \n \n\n\n \n Safaya, A.; Abdullatif, M.; and Yuret, D.\n\n\n \n\n\n\n 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@misc{safaya2020kuisail,\n    author = {Ali Safaya and Moutasem Abdullatif and Deniz Yuret},\n    title = {KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media},\n    year = {2020},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n \n Joint Training with Semantic Role Labeling for Better Generalization in Natural Language Inference.\n \n \n \n \n\n\n \n Cengiz, C.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the 5th Workshop on Representation Learning for NLP, pages 78–88, 2020. \n \n\n\n\n
\n\n\n\n \n \n \"JointPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{cengiz-yuret-2020-joint,\n    author = {Cengiz, Cemil and Yuret, Deniz},\n    title = {Joint Training with Semantic Role Labeling for Better Generalization in Natural Language Inference},\n    booktitle = {Proceedings of the 5th Workshop on Representation Learning for NLP},\n    year = {2020},\n    url = {https://www.aclweb.org/anthology/2020.repl4nlp-1.11},\n    pages = {78--88},\n    abstract = {End-to-end models trained on natural language inference (NLI) datasets show low generalization on out-of-distribution evaluation sets. The models tend to learn shallow heuristics due to dataset biases. The performance decreases dramatically on diagnostic sets measuring compositionality or robustness against simple heuristics. Existing solutions for this problem employ dataset augmentation which has the drawbacks of being applicable to only a limited set of adversaries and at worst hurting the model performance on other adversaries not included in the augmentation set. Instead, our proposed solution is to improve sentence understanding (hence out-of-distribution generalization) with joint learning of explicit semantics. We show that a BERT based model trained jointly on English semantic role labeling (SRL) and NLI achieves significantly higher performance on external evaluation sets measuring generalization performance.},\n    keywords = {NLP},\n}\n\n
\n
\n\n\n
\n End-to-end models trained on natural language inference (NLI) datasets show low generalization on out-of-distribution evaluation sets. The models tend to learn shallow heuristics due to dataset biases. The performance decreases dramatically on diagnostic sets measuring compositionality or robustness against simple heuristics. Existing solutions for this problem employ dataset augmentation which has the drawbacks of being applicable to only a limited set of adversaries and at worst hurting the model performance on other adversaries not included in the augmentation set. Instead, our proposed solution is to improve sentence understanding (hence out-of-distribution generalization) with joint learning of explicit semantics. We show that a BERT based model trained jointly on English semantic role labeling (SRL) and NLI achieves significantly higher performance on external evaluation sets measuring generalization performance.\n
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\n \n\n \n \n \n \n \n CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions.\n \n \n \n\n\n \n Ates, T.; Atesoglu, M. S.; Yigit, C.; Kesen, I.; Kobas, M.; Erdem, E.; Erdem, A.; Goksun, T.; and Yuret, D.\n\n\n \n\n\n\n 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@misc{ates2020craft,\n    author = {Tayfun Ates and Muhammed Samil Atesoglu and Cagatay Yigit and Ilker Kesen and Mert Kobas and Erkut Erdem and Aykut Erdem and Tilbe Goksun and Deniz Yuret},\n    title = {CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions},\n    year = {2020},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n \n Tiling-Based Programming Model for Structured Grids on GPU Clusters.\n \n \n \n \n\n\n \n Bastem, B.; and Unat, D.\n\n\n \n\n\n\n In Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, pages 43–51, New York, NY, USA, 2020. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n \"Tiling-BasedPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{10.1145/3368474.3368485,\n    author = {Bastem, Burak and Unat, Didem},\n    title = {Tiling-Based Programming Model for Structured Grids on GPU Clusters},\n    year = {2020},\n    isbn = {9781450372367},\n    publisher = {Association for Computing Machinery},\n    address = {New York, NY, USA},\n    url = {https://doi.org/10.1145/3368474.3368485},\n    doi = {10.1145/3368474.3368485},\n    abstract = {Currently, more than 25% of supercomputers employ GPUs due to their massively parallel and power-efficient architectures. However, programming GPUs efficiently in a large scale system is a demanding task not only for computational scientists but also for programming experts as multi-GPU programming requires managing distinct address spaces, generating GPU-specific code and handling inter-device communication. To ease the programming effort, we propose a tiling-based high-level GPU programming model for structured grid problems. The model abstracts data decomposition, memory management and generation of GPU specific code, and hides all types of data transfer overheads. We demonstrate the effectiveness of the programming model on a heat simulation and a real-life cardiac modeling on a single GPU, on a single node with multiple-GPUs and multiple-nodes with multiple-GPUs. We also present performance comparisons under different hardware and software configurations. The results show that the programming model successfully overlaps communication and provides good speedup on 192 GPUs.},\n    booktitle = {Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region},\n    pages = {43–51},\n    keywords = {multi-GPU,GPU programming,GPU streams,tiling,communication overlap,GPU cluster,SAI},\n}\n\n
\n
\n\n\n
\n Currently, more than 25% of supercomputers employ GPUs due to their massively parallel and power-efficient architectures. However, programming GPUs efficiently in a large scale system is a demanding task not only for computational scientists but also for programming experts as multi-GPU programming requires managing distinct address spaces, generating GPU-specific code and handling inter-device communication. To ease the programming effort, we propose a tiling-based high-level GPU programming model for structured grid problems. The model abstracts data decomposition, memory management and generation of GPU specific code, and hides all types of data transfer overheads. We demonstrate the effectiveness of the programming model on a heat simulation and a real-life cardiac modeling on a single GPU, on a single node with multiple-GPUs and multiple-nodes with multiple-GPUs. We also present performance comparisons under different hardware and software configurations. The results show that the programming model successfully overlaps communication and provides good speedup on 192 GPUs.\n
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\n \n\n \n \n \n \n \n \n Adaptive Level Binning: A New Algorithm for Solving Sparse Triangular Systems.\n \n \n \n \n\n\n \n Yılmaz, B.; Sipahioğrlu, B.; Ahmad, N.; and Unat, D.\n\n\n \n\n\n\n In Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, pages 188–198, New York, NY, USA, 2020. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n \"AdaptivePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{10.1145/3368474.3368486,\n    author = {Y\\i{}lmaz, Buse and Sipahio\\u{g}rlu, Bu\\u{g}rra and Ahmad, Najeeb and Unat, Didem},\n    title = {Adaptive Level Binning: A New Algorithm for Solving Sparse Triangular Systems},\n    year = {2020},\n    isbn = {9781450372367},\n    publisher = {Association for Computing Machinery},\n    address = {New York, NY, USA},\n    url = {https://doi.org/10.1145/3368474.3368486},\n    doi = {10.1145/3368474.3368486},\n    abstract = {Sparse triangular solve (SpTRSV) is an important scientific kernel used in several applications such as preconditioners for Krylov methods. Parallelizing SpTRSV on multi-core systems is challenging since it exhibits limited parallelism due to computational dependencies and introduces high parallelization overhead due to finegrained and unbalanced nature of workloads. We propose a novel method, named Adaptive Level Binning (ALB), that addresses these challenges by eliminating redundant synchronization points and adapting the work granularity with an efficient load balancing strategy. Similar to the commonly used level-set methods for solving SpTRSV, ALB constructs level-sets of rows, where each level can be computed in parallel. Differently, ALB bins rows to levels adaptively and reduces redundant dependencies between rows. On an Intel® Xeon® Gold 6148 processor and NVIDIA® Tesla V100 GPU, ALB obtains 1.83x speedup on average and up to 5.28x speedup over Intel MKL and, over NVIDIA cuSPARSE, an average speedup of 2.80x and a maximum speedup of 39.40x for 29 matrices selected from Suite Sparse Matrix Collection.},\n    booktitle = {Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region},\n    pages = {188–198},\n    keywords = {sparse triangular solvers,CPU,fine-grained parallelism,level-set,SAI},\n}\n\n
\n
\n\n\n
\n Sparse triangular solve (SpTRSV) is an important scientific kernel used in several applications such as preconditioners for Krylov methods. Parallelizing SpTRSV on multi-core systems is challenging since it exhibits limited parallelism due to computational dependencies and introduces high parallelization overhead due to finegrained and unbalanced nature of workloads. We propose a novel method, named Adaptive Level Binning (ALB), that addresses these challenges by eliminating redundant synchronization points and adapting the work granularity with an efficient load balancing strategy. Similar to the commonly used level-set methods for solving SpTRSV, ALB constructs level-sets of rows, where each level can be computed in parallel. Differently, ALB bins rows to levels adaptively and reduces redundant dependencies between rows. On an Intel® Xeon® Gold 6148 processor and NVIDIA® Tesla V100 GPU, ALB obtains 1.83x speedup on average and up to 5.28x speedup over Intel MKL and, over NVIDIA cuSPARSE, an average speedup of 2.80x and a maximum speedup of 39.40x for 29 matrices selected from Suite Sparse Matrix Collection.\n
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\n \n\n \n \n \n \n \n \n ComScribe: Identifying Intra-node GPU Communication.\n \n \n \n \n\n\n \n Akhtar, P.; Qararyah, F. M.; and Unat, D.\n\n\n \n\n\n\n In Benchmarking, Measuring, and Optimizing - Third BenchCouncil Internationa Symposium, Bench 2020, Virtual Event, November 15-16, 2020, Revised Selected Papers, 2020. \n \n\n\n\n
\n\n\n\n \n \n \"ComScribe:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{DBLP:conf/bench/AkhtarTQU20,\n    author = {Palwisha Akhtar and Fareed Mohammad Qararyah and Didem Unat},\n    title = {ComScribe: Identifying Intra-node {GPU} Communication},\n    booktitle = {Benchmarking, Measuring, and Optimizing - Third BenchCouncil Internationa Symposium, Bench 2020, Virtual Event, November 15-16, 2020, Revised                Selected Papers},\n    year = {2020},\n    url = {https://doi.org/10.1007/978-3-030-71058-3\\_10},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n \n Can learned frame prediction compete with block motion compensation for video coding?.\n \n \n \n \n\n\n \n Sulun, S.; and Tekalp, A. M.\n\n\n \n\n\n\n Signal, Image and Video Processing, 15(2): 401–410. Aug 2020.\n \n\n\n\n
\n\n\n\n \n \n \"CanPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Sulun_2020,\n    title = {Can learned frame prediction compete with block motion compensation for video coding?},\n    volume = {15},\n    issn = {1863-1711},\n    url = {http://dx.doi.org/10.1007/s11760-020-01751-y},\n    doi = {10.1007/s11760-020-01751-y},\n    number = {2},\n    journal = {Signal, Image and Video Processing},\n    publisher = {Springer Science and Business Media LLC},\n    author = {Sulun, Serkan and Tekalp, A. Murat},\n    year = {2020},\n    month = {Aug},\n    pages = {401–410},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n \n Realizing a Low-Power Head-Mounted Phase-Only Holographic Display by Light-Weight Compression.\n \n \n \n \n\n\n \n Soner, B.; Ulusoy, E.; Tekalp, A. M.; and Urey, H.\n\n\n \n\n\n\n IEEE Transactions on Image Processing, 29: 4505–4515. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"RealizingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Soner_2020,\n    title = {Realizing a Low-Power Head-Mounted Phase-Only Holographic Display by Light-Weight Compression},\n    volume = {29},\n    issn = {1941-0042},\n    url = {http://dx.doi.org/10.1109/TIP.2020.2972112},\n    doi = {10.1109/tip.2020.2972112},\n    journal = {IEEE Transactions on Image Processing},\n    publisher = {Institute of Electrical and Electronics Engineers (IEEE)},\n    author = {Soner, Burak and Ulusoy, Erdem and Tekalp, A. Murat and Urey, Hakan},\n    year = {2020},\n    pages = {4505–4515},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n \n Kart-ON: Affordable Early Programming Education with Shared Smartphones and Easy-to-Find Materials.\n \n \n \n \n\n\n \n Sabuncuoğlu, A.; and Sezgin, M.\n\n\n \n\n\n\n In Proceedings of the 25th International Conference on Intelligent User Interfaces Companion, of IUI '20, pages 116–117, New York, NY, USA, 2020. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n \"Kart-ON:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{10.1145/3379336.3381472,\n    author = {Sabuncuo\\u{g}lu, Alpay and Sezgin, Metin},\n    title = {Kart-ON: Affordable Early Programming Education with Shared Smartphones and Easy-to-Find Materials},\n    year = {2020},\n    isbn = {9781450375139},\n    publisher = {Association for Computing Machinery},\n    address = {New York, NY, USA},\n    url = {https://doi.org/10.1145/3379336.3381472},\n    doi = {10.1145/3379336.3381472},\n    abstract = {Programming education has become an integral part of the primary school curriculum. However, most programming practices rely heavily on computers and electronics which causes inequalities across contexts with different socioeconomic levels. This demo introduces a new and convenient way of using tangibles for coding in classrooms. Our programming environment, Kart-ON, is designed as an affordable means to increase collaboration among students and decrease dependency on screen-based interfaces. Kart-ON is a tangible programming language that uses everyday objects such as paper, pen, fabrics as programming objects and employs a mobile phone as the compiler. Our preliminary studies with children (n=16, mage=12) show that Kart-ON boosts active and collaborative student participation in the tangible programming task, which is especially valuable in crowded classrooms with limited access to computational devices.},\n    booktitle = {Proceedings of the 25th International Conference on Intelligent User Interfaces Companion},\n    pages = {116–117},\n    keywords = {Affordable tangible programming,Collaborative classroom,HCI},\n    series = {IUI '20},\n}\n\n
\n
\n\n\n
\n Programming education has become an integral part of the primary school curriculum. However, most programming practices rely heavily on computers and electronics which causes inequalities across contexts with different socioeconomic levels. This demo introduces a new and convenient way of using tangibles for coding in classrooms. Our programming environment, Kart-ON, is designed as an affordable means to increase collaboration among students and decrease dependency on screen-based interfaces. Kart-ON is a tangible programming language that uses everyday objects such as paper, pen, fabrics as programming objects and employs a mobile phone as the compiler. Our preliminary studies with children (n=16, mage=12) show that Kart-ON boosts active and collaborative student participation in the tangible programming task, which is especially valuable in crowded classrooms with limited access to computational devices.\n
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\n \n\n \n \n \n \n \n \n Data-driven vibrotactile rendering of digital buttons on touchscreens.\n \n \n \n \n\n\n \n Sadia, B.; Emgin, S. E.; Sezgin, T. M.; and Basdogan, C.\n\n\n \n\n\n\n International Journal of Human-Computer Studies, 135: 102363. Mar 2020.\n \n\n\n\n
\n\n\n\n \n \n \"Data-drivenPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Sadia_2020,\n    title = {Data-driven vibrotactile rendering of digital buttons on touchscreens},\n    volume = {135},\n    issn = {1071-5819},\n    url = {http://dx.doi.org/10.1016/j.ijhcs.2019.09.005},\n    doi = {10.1016/j.ijhcs.2019.09.005},\n    journal = {International Journal of Human-Computer Studies},\n    publisher = {Elsevier BV},\n    author = {Sadia, Bushra and Emgin, Senem Ezgi and Sezgin, T. Metin and Basdogan, Cagatay},\n    year = {2020},\n    month = {Mar},\n    pages = {102363},\n    keywords = {HCI},\n}\n\n
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\n \n\n \n \n \n \n \n LogDos: A Novel Logging-based DDoS Prevention Mechanism in Path Identifier-Based Information Centric Networks.\n \n \n \n\n\n \n Al-Duwairi, B.; Ozkasap, O.; Uysal, A.; Kocaogullar, C.; and Yildirim, K.\n\n\n \n\n\n\n 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@misc{alduwairi2020logdos,\n    title = {LogDos: A Novel Logging-based DDoS Prevention Mechanism in Path Identifier-Based Information Centric Networks},\n    author = {Basheer Al-Duwairi and Oznur Ozkasap and Ahmet Uysal and Ceren Kocaogullar and Kaan Yildirim},\n    year = {2020},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n EdgeKV: Decentralized, scalable, and consistent storage for the edge.\n \n \n \n\n\n \n Sonbol, K.; Özkasap, Ö.; Al-Oqily, I.; and Aloqaily, M.\n\n\n \n\n\n\n 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@misc{sonbol2020edgekv,\n    title = {EdgeKV: Decentralized, scalable, and consistent storage for the edge},\n    author = {Karim Sonbol and {\\"O}znur {\\"O}zkasap and Ibrahim Al-Oqily and Moayad Aloqaily},\n    year = {2020},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Demo: Skip Graph Middleware Implementation.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Nayal, N.; Hamdan, S. S.; Sahin, A. U.; Özkasap, Ö.; and Küpçü, A.\n\n\n \n\n\n\n In International Symposium on Reliable Distributed Systems, SRDS 2020, Shanghai, China, September 21-24, 2020, 2020. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{DBLP:conf/srds/Hassanzadeh-Nazarabadi20,\n    author = {Yahya Hassanzadeh{-}Nazarabadi and Nazir Nayal and                Shadi Sameh Hamdan and                Ali Utkan Sahin and                {\\"{O}}znur {\\"{O}}zkasap and Alptekin K{\\"{u}}p{\\c{c}}{\\"{u}}},\n    title = {Demo: Skip Graph Middleware Implementation},\n    booktitle = {International Symposium on Reliable Distributed Systems, {SRDS} 2020,                Shanghai, China, September 21-24, 2020},\n    year = {2020},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Demo: A Proof-of-Concept Implementation of Guard Secure Routing Protocol.\n \n \n \n\n\n \n Taheri-Boshrooyeh, S.; Şahin, A. U.; Hassanzadeh-Nazarabadi, Y.; and Özkasap, Ö.\n\n\n \n\n\n\n 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@misc{taheriboshrooyeh2020demo,\n    title = {Demo: A Proof-of-Concept Implementation of Guard Secure Routing Protocol},\n    author = {Sanaz Taheri-Boshrooyeh and Ali Utkan {\\c{S}}ahin and Yahya Hassanzadeh-Nazarabadi and {\\"O}znur {\\"O}zkasap},\n    year = {2020},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Joulin: Blockchain-based P2P Energy Trading Using Smart Contracts.\n \n \n \n\n\n \n Perk, B.; Bayraktaroglu, C.; Dogu, E. D.; Ali, F. S.; and Özkasap, Ö.\n\n\n \n\n\n\n In IEEE Symposium on Computers and Communications, ISCC 2020, Rennes, France, July 7-10, 2020, 2020. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{DBLP:conf/iscc/PerkBDAO20,\n    title = {Joulin: Blockchain-based {P2P} Energy Trading Using Smart Contracts},\n    booktitle = {{IEEE} Symposium on Computers and Communications, {ISCC} 2020, Rennes,  France, July 7-10, 2020},\n    year = {2020},\n    keywords = {SAI},\n    author = {Berrak Perk and Can Bayraktaroglu and Engin Deniz Dogu and Faizan Safdar Ali and  {\\"{O}}znur {\\"{O}}zkasap},\n}\n\n
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\n \n\n \n \n \n \n \n \n Privado: Privacy-Preserving Group-Based Advertising Using Multiple Independent Social Network Providers.\n \n \n \n \n\n\n \n Boshrooyeh, S. T.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n ACM Trans. Priv. Secur.. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"Privado:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{10.1145/3386154,\n    author = {Boshrooyeh, Sanaz Taheri and K\\"{u}p\\c{c}\\"{u}, Alptekin and \\"{O}zkasap, \\"{O}znur},\n    title = {Privado: Privacy-Preserving Group-Based Advertising Using Multiple Independent Social Network Providers},\n    year = {2020},\n    publisher = {Association for Computing Machinery},\n    url = {https://doi.org/10.1145/3386154},\n    doi = {10.1145/3386154},\n    abstract = {Online Social Networks (OSNs) offer free storage and social networking services through which users can communicate personal information with one another. The personal information of the users collected by the OSN provider comes with privacy problems when being monetized for advertising purposes. To protect user privacy, existing studies propose utilizing data encryption that immediately prevents OSNs from monetizing users data and hence leaves secure OSNs with no convincing commercial model. To address this problem, we propose Privado as a privacy-preserving group-based advertising mechanism to be integrated into secure OSNs to re-empower monetizing ability. Privado is run by N servers, each provided by an independent provider. User privacy is protected against an active malicious adversary controlling N − 1 providers, all the advertisers, and a large fraction of the users. We base our design on the group-based advertising notion to protect user privacy, which is not possible in the personalized variant. Our design also delivers advertising transparency; the procedure of identifying target customers is operated solely by the OSN servers without getting users and advertisers involved. We carry out experiments to examine the advertising running time under various number of servers and group sizes. We also argue about the optimum number of servers with respect to user privacy and advertising running time.},\n    journal = {ACM Trans. Priv. Secur.},\n    keywords = {online social networks,privacy-preserving advertising,advertising,malicious adversary,active adversary,privacy,Unlinkability,SAI},\n}\n\n
\n
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\n Online Social Networks (OSNs) offer free storage and social networking services through which users can communicate personal information with one another. The personal information of the users collected by the OSN provider comes with privacy problems when being monetized for advertising purposes. To protect user privacy, existing studies propose utilizing data encryption that immediately prevents OSNs from monetizing users data and hence leaves secure OSNs with no convincing commercial model. To address this problem, we propose Privado as a privacy-preserving group-based advertising mechanism to be integrated into secure OSNs to re-empower monetizing ability. Privado is run by N servers, each provided by an independent provider. User privacy is protected against an active malicious adversary controlling N − 1 providers, all the advertisers, and a large fraction of the users. We base our design on the group-based advertising notion to protect user privacy, which is not possible in the personalized variant. Our design also delivers advertising transparency; the procedure of identifying target customers is operated solely by the OSN servers without getting users and advertisers involved. We carry out experiments to examine the advertising running time under various number of servers and group sizes. We also argue about the optimum number of servers with respect to user privacy and advertising running time.\n
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\n \n\n \n \n \n \n \n Peer-to-Peer Blockchain based Energy Trading.\n \n \n \n\n\n \n Ali, F. S.; Aloqaily, M.; Alfandi, O.; and Özkasap, Ö.\n\n\n \n\n\n\n CoRR. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{DBLP:journals/corr/abs-2001-00746,\n    author = {Faizan Safdar Ali and                Moayad Aloqaily and                Omar Alfandi and                {\\"{O}}znur {\\"{O}}zkasap},\n    title = {Peer-to-Peer Blockchain based Energy Trading},\n    journal = {CoRR},\n    year = {2020},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n \n Identification of potential inhibitors of human methionine aminopeptidase (type II) for cancer therapy: Structure-based virtual screening, ADMET prediction and molecular dynamics studies.\n \n \n \n \n\n\n \n Weako, J.; Uba, A. I.; Keskin, Ö.; Gürsoy, A.; and Yelekçi, K.\n\n\n \n\n\n\n Computational biology and chemistry, 86: 107244. June 2020.\n \n\n\n\n
\n\n\n\n \n \n \"IdentificationPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{PMID:32252002,\n    title = {Identification of potential inhibitors of human methionine aminopeptidase (type II) for cancer therapy: Structure-based virtual screening, ADMET prediction and molecular dynamics studies},\n    author = {Weako, Jackson and Uba, Abdullahi Ibrahim and Keskin, {\\"O}zlem and G{\\"u}rsoy, Attila and Yelek{\\c{c}}i, Kemal},\n    doi = {10.1016/j.compbiolchem.2020.107244},\n    volume = {86},\n    month = {June},\n    year = {2020},\n    journal = {Computational biology and chemistry},\n    issn = {1476-9271},\n    pages = {107244},\n    abstract = {Methionine Aminopeptidases MetAPs are divalent-cofactor dependent enzymes that are responsible for the cleavage of the initiator Methionine from the nascent polypeptides. MetAPs are classified into two isoforms: namely, MetAP1 and MetAP2. Several studies have revealed that MetAP2 is upregulated in various cancers, and its inhibition has shown to suppress abnormal or excessive blood vessel formation and tumor growth in model organisms. Clinical studies show that the natural product fumagillin, and its analogs are potential inhibitors of MetAP2. However, due to their poor pharmacokinetic properties and neurotoxicities in clinical studies, their further developments have received a great setback. Here, we apply structure-based virtual screening and molecular dynamics methods to identify a new class of potential inhibitors for MetAP2. We screened Otava's Chemical Library, which consists of about 3 200 000 tangible-chemical compounds, and meticulously selected the top 10 of these compounds based on their inhibitory potentials against MetAP2. The top hit compounds subjected to ADMET predictor using 3 independent ADMET prediction programs, were found to be drug-like. To examine the stability of ligand binding mode, and efficacy, the unbound form of MetAP2, its complexes with fumagillin, spiroepoxytriazole, and the best promising compounds compound-3369841 and compound-3368818 were submitted to 100 ns molecular dynamics simulation. Like fumagillin, spiroepoxytriazole, and both compound-3369841 and compound-3368818 showed stable binding mode over time during the simulations. Taken together, these uninherited-fumagillin compounds may serve as new class of inhibitors or provide scaffolds for further optimization towards the design of more potent MetAP2 inhibitors -development of such inhibitors would be essential strategy against various cancer types.},\n    url = {https://doi.org/10.1016/j.compbiolchem.2020.107244},\n    keywords = {CBM},\n}\n\n
\n
\n\n\n
\n Methionine Aminopeptidases MetAPs are divalent-cofactor dependent enzymes that are responsible for the cleavage of the initiator Methionine from the nascent polypeptides. MetAPs are classified into two isoforms: namely, MetAP1 and MetAP2. Several studies have revealed that MetAP2 is upregulated in various cancers, and its inhibition has shown to suppress abnormal or excessive blood vessel formation and tumor growth in model organisms. Clinical studies show that the natural product fumagillin, and its analogs are potential inhibitors of MetAP2. However, due to their poor pharmacokinetic properties and neurotoxicities in clinical studies, their further developments have received a great setback. Here, we apply structure-based virtual screening and molecular dynamics methods to identify a new class of potential inhibitors for MetAP2. We screened Otava's Chemical Library, which consists of about 3 200 000 tangible-chemical compounds, and meticulously selected the top 10 of these compounds based on their inhibitory potentials against MetAP2. The top hit compounds subjected to ADMET predictor using 3 independent ADMET prediction programs, were found to be drug-like. To examine the stability of ligand binding mode, and efficacy, the unbound form of MetAP2, its complexes with fumagillin, spiroepoxytriazole, and the best promising compounds compound-3369841 and compound-3368818 were submitted to 100 ns molecular dynamics simulation. Like fumagillin, spiroepoxytriazole, and both compound-3369841 and compound-3368818 showed stable binding mode over time during the simulations. Taken together, these uninherited-fumagillin compounds may serve as new class of inhibitors or provide scaffolds for further optimization towards the design of more potent MetAP2 inhibitors -development of such inhibitors would be essential strategy against various cancer types.\n
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\n \n\n \n \n \n \n \n Beyond the heterodimer model for mineralocorticoid and glucocorticoid receptor interactions in nuclei and at DNA.\n \n \n \n\n\n \n Pooley, J.; Rivers, C.; Kilcooley, M.; Paul, S.; Cavga, A.; Kershaw, Y.; Muratcioglu, S.; Gursoy, A.; Keskin, O.; and Lightman, S.\n\n\n \n\n\n\n PLoS ONE, 15. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{b01431ce9b1e48a7b4452b7ad91e552a,\n    title = {Beyond the heterodimer model for mineralocorticoid and glucocorticoid receptor interactions in nuclei and at DNA.},\n    abstract = {Glucocorticoid (GR) and mineralocorticoid receptors (MR) are believed to classically bind DNA as homodimers or MR-GR heterodimers to influence gene regulation in response to pulsatile basal or stress-evoked glucocorticoid secretion. Pulsed corticosterone presentation reveals MR and GR co-occupy DNA only at the peaks of glucocorticoid oscillations, allowing interaction. GR DNA occupancy was pulsatile, while MR DNA occupancy was prolonged through the inter-pulse interval. In mouse mammary 3617 cells MR-GR interacted in the nucleus and at a chromatin-associated DNA binding site. Interactions occurred irrespective of ligand type and receptors formed complexes of higher order than heterodimers. We also detected MR-GR interactions ex-vivo in rat hippocampus. An expanded range of MR-GR interactions predicts structural allostery allowing a variety of transcriptional outcomes and is applicable to the multiple tissue types that co-express both receptors in the same cells whether activated by the same or different hormones.},\n    author = {John Pooley and Rivers, {Caroline A} and Michael Kilcooley and Paul, {Susana N} and Cavga, {Ayse Derya} and Kershaw, {Yvonne M} and Serena Muratcioglu and Attila Gursoy and Ozlem Keskin and Lightman, {Stafford L}},\n    year = {2020},\n    doi = {10.1371/journal.pone.0227520},\n    volume = {15},\n    journal = {PLoS ONE},\n    publisher = {Public Library of Science},\n    keywords = {CBM},\n}\n\n
\n
\n\n\n
\n Glucocorticoid (GR) and mineralocorticoid receptors (MR) are believed to classically bind DNA as homodimers or MR-GR heterodimers to influence gene regulation in response to pulsatile basal or stress-evoked glucocorticoid secretion. Pulsed corticosterone presentation reveals MR and GR co-occupy DNA only at the peaks of glucocorticoid oscillations, allowing interaction. GR DNA occupancy was pulsatile, while MR DNA occupancy was prolonged through the inter-pulse interval. In mouse mammary 3617 cells MR-GR interacted in the nucleus and at a chromatin-associated DNA binding site. Interactions occurred irrespective of ligand type and receptors formed complexes of higher order than heterodimers. We also detected MR-GR interactions ex-vivo in rat hippocampus. An expanded range of MR-GR interactions predicts structural allostery allowing a variety of transcriptional outcomes and is applicable to the multiple tissue types that co-express both receptors in the same cells whether activated by the same or different hormones.\n
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\n \n\n \n \n \n \n \n \n The structural basis of the oncogenic mutant K-Ras4B homodimers.\n \n \n \n \n\n\n \n Kosoglu, K.; Omur, M. E.; Jang, H.; Nussinov, R.; Keskin, O.; and Gursoy, A.\n\n\n \n\n\n\n bioRxiv. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Kosoglu2020.09.07.285783,\n    author = {Kosoglu, Kayra and Omur, Meltem Eda and Jang, Hyunbum and Nussinov, Ruth and Keskin, Ozlem and Gursoy, Attila},\n    title = {The structural basis of the oncogenic mutant K-Ras4B homodimers},\n    year = {2020},\n    doi = {10.1101/2020.09.07.285783},\n    publisher = {Cold Spring Harbor Laboratory},\n    abstract = {Ras proteins activate their effectors through physical interactions in response to the various extracellular stimuli at the plasma membrane. Oncogenic Ras forms dimer and nanoclusters at the plasma membrane, boosting the downstream MAPK signal. It was reported that K-Ras4B can dimerize through two major interfaces: (i) the effector lobe interface, mapped to Switch I and effector binding regions; (ii) the allosteric lobe interface involving α3 and α4 helices. Recent experiments showed that constitutively active, oncogenic mutant K-Ras4BG12D dimers are enriched in the plasma membrane. Here, we perform molecular dynamics simulations of K-Ras4BG12D homodimers aiming to quantify the two major interfaces in atomic level. To examine the effect of mutations on dimerization, two double mutations, K101D/R102E on the allosteric lobe and R41E/K42D on the effector lobe interfaces were added to the K-Ras4BG12D dimer simulations. We observed that the effector lobe K-Ras4BG12D dimer is stable, while the allosteric lobe dimer alters its helical interface during the simulations, presenting multiple conformations. The K101D/R102E mutations slightly weakens the allosteric lobe interface. However, the R41E/K42D mutations disrupt the effector lobe interface. Using the homo-oligomers prediction server, we obtained trimeric, tetrameric, and pentameric complexes with the allosteric lobe K-Ras4BG12D dimers. However, the allosteric lobe dimer with the K101D/R102E mutations is not capable of generating multiple higher order structures. Our detailed interface analysis may help to develop inhibitor design targeting functional Ras dimerization and high order oligomerization at the membrane signaling platform.},\n    url = {https://www.biorxiv.org/content/early/2020/09/07/2020.09.07.285783},\n    journal = {bioRxiv},\n    keywords = {CBM},\n}\n\n
\n
\n\n\n
\n Ras proteins activate their effectors through physical interactions in response to the various extracellular stimuli at the plasma membrane. Oncogenic Ras forms dimer and nanoclusters at the plasma membrane, boosting the downstream MAPK signal. It was reported that K-Ras4B can dimerize through two major interfaces: (i) the effector lobe interface, mapped to Switch I and effector binding regions; (ii) the allosteric lobe interface involving α3 and α4 helices. Recent experiments showed that constitutively active, oncogenic mutant K-Ras4BG12D dimers are enriched in the plasma membrane. Here, we perform molecular dynamics simulations of K-Ras4BG12D homodimers aiming to quantify the two major interfaces in atomic level. To examine the effect of mutations on dimerization, two double mutations, K101D/R102E on the allosteric lobe and R41E/K42D on the effector lobe interfaces were added to the K-Ras4BG12D dimer simulations. We observed that the effector lobe K-Ras4BG12D dimer is stable, while the allosteric lobe dimer alters its helical interface during the simulations, presenting multiple conformations. The K101D/R102E mutations slightly weakens the allosteric lobe interface. However, the R41E/K42D mutations disrupt the effector lobe interface. Using the homo-oligomers prediction server, we obtained trimeric, tetrameric, and pentameric complexes with the allosteric lobe K-Ras4BG12D dimers. However, the allosteric lobe dimer with the K101D/R102E mutations is not capable of generating multiple higher order structures. Our detailed interface analysis may help to develop inhibitor design targeting functional Ras dimerization and high order oligomerization at the membrane signaling platform.\n
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\n \n\n \n \n \n \n \n Embedding Alternative Conformations of Proteins in Protein-Protein Interaction Networks.\n \n \n \n\n\n \n Halakou, F.; Gürsoy, A.; and Keskin, - O.\n\n\n \n\n\n\n In Protein-Protein Interaction Networks, Methods and Protocols. Springer, 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@incollection{DBLP:series/mimb/HalakouGK20,\n    author = {Farideh Halakou and  Attila G{\\"{u}}rsoy and- Ozlem Keskin},\n    title = {Embedding Alternative Conformations of Proteins in Protein-Protein Interaction Networks},\n    booktitle = {Protein-Protein Interaction Networks, Methods and Protocols},\n    publisher = {Springer},\n    year = {2020},\n    keywords = {CBM},\n}\n\n
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\n \n\n \n \n \n \n \n \n Time and frequency based sparse bounded component analysis algorithms for convolutive mixtures.\n \n \n \n \n\n\n \n Babatas, E.; and Erdogan, A. T.\n\n\n \n\n\n\n Signal Processing, 173: 107590. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"TimePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@article{BABATAS2020107590,\n    title = {Time and frequency based sparse bounded component analysis algorithms for convolutive mixtures},\n    journal = {Signal Processing},\n    volume = {173},\n    pages = {107590},\n    year = {2020},\n    issn = {0165-1684},\n    doi = {https://doi.org/10.1016/j.sigpro.2020.107590},\n    url = {https://www.sciencedirect.com/science/article/pii/S016516842030133X},\n    author = {Eren Babatas and Alper T. Erdogan},\n    keywords = {Convolutive blind source separation,Bounded component analysis,Sparse component analysis,Sparse bounded component analysis,Blind speech separation,ML},\n    abstract = {In this paper, we introduce time-domain and frequency-domain versions of a new Blind Source Separation (BSS) approach to extract bounded magnitude sparse sources from convolutive mixtures. We derive algorithms by maximization of the proposed objective functions that are defined in a completely deterministic framework, and prove that global maximums of the objective functions yield perfect separation under suitable conditions. The derived algorithms can be applied to temporal or spatially dependent sources as well as independent sources. We provide experimental results to demonstrate some benefits of the approach, also including an application on blind speech separation.},\n}\n\n
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\n In this paper, we introduce time-domain and frequency-domain versions of a new Blind Source Separation (BSS) approach to extract bounded magnitude sparse sources from convolutive mixtures. We derive algorithms by maximization of the proposed objective functions that are defined in a completely deterministic framework, and prove that global maximums of the objective functions yield perfect separation under suitable conditions. The derived algorithms can be applied to temporal or spatially dependent sources as well as independent sources. We provide experimental results to demonstrate some benefits of the approach, also including an application on blind speech separation.\n
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\n \n\n \n \n \n \n \n \n Blind Bounded Source Separation Using Neural Networks with Local Learning Rules.\n \n \n \n \n\n\n \n Erdogan, A. T.; and Pehlevan, C.\n\n\n \n\n\n\n ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2020.\n \n\n\n\n
\n\n\n\n \n \n \"BlindPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Erdogan_2020,\n    title = {Blind Bounded Source Separation Using Neural Networks with Local Learning Rules},\n    isbn = {9781509066315},\n    url = {http://dx.doi.org/10.1109/ICASSP40776.2020.9053114},\n    doi = {10.1109/icassp40776.2020.9053114},\n    journal = {ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    publisher = {IEEE},\n    author = {Erdogan, Alper T. and Pehlevan, Cengiz},\n    year = {2020},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n \n Hedging static saliency models to predict dynamic saliency.\n \n \n \n \n\n\n \n Kavak, Y.; Erdem, E.; and Erdem, A.\n\n\n \n\n\n\n Signal Processing: Image Communication, 81: 115694. 2020.\n \n\n\n\n
\n\n\n\n \n \n \"HedgingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{KAVAK2020115694,\n    title = {Hedging static saliency models to predict dynamic saliency},\n    journal = {Signal Processing: Image Communication},\n    volume = {81},\n    pages = {115694},\n    year = {2020},\n    issn = {0923-5965},\n    doi = {https://doi.org/10.1016/j.image.2019.115694},\n    url = {https://www.sciencedirect.com/science/article/pii/S0923596518311846},\n    author = {Yasin Kavak and Erkut Erdem and Aykut Erdem},\n    keywords = {Dynamic saliency,Hedge algorithm,Decision theoretic online learning,Feature integration,CV},\n    abstract = {In recent years, many computational models for saliency prediction have been introduced. For dynamic scenes, the existing models typically combine different feature maps extracted from spatial and temporal domains either by following generic integration strategies such as averaging or winners take all or using machine learning techniques to set each feature’s importance. Rather than resorting to these fixed feature integration schemes, in this paper, we propose a novel weakly supervised dynamic saliency model called HedgeSal, which is based on a decision-theoretic online learning scheme. Our framework uses two pretrained deep static saliency models as experts to extract individual saliency maps from appearance and motion streams, and then generates the final saliency map by weighted decisions of all these models. As visual characteristics of dynamic scenes constantly vary, the models providing consistently good predictions in the past are automatically assigned higher weights, allowing each expert to adjust itself to the current conditions. We demonstrate the effectiveness of our model on the CRCNS, UCFSports and CITIUS datasets.},\n}\n\n
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\n In recent years, many computational models for saliency prediction have been introduced. For dynamic scenes, the existing models typically combine different feature maps extracted from spatial and temporal domains either by following generic integration strategies such as averaging or winners take all or using machine learning techniques to set each feature’s importance. Rather than resorting to these fixed feature integration schemes, in this paper, we propose a novel weakly supervised dynamic saliency model called HedgeSal, which is based on a decision-theoretic online learning scheme. Our framework uses two pretrained deep static saliency models as experts to extract individual saliency maps from appearance and motion streams, and then generates the final saliency map by weighted decisions of all these models. As visual characteristics of dynamic scenes constantly vary, the models providing consistently good predictions in the past are automatically assigned higher weights, allowing each expert to adjust itself to the current conditions. We demonstrate the effectiveness of our model on the CRCNS, UCFSports and CITIUS datasets.\n
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\n \n\n \n \n \n \n \n Machine learning-enabled multiplexed microfluidic sensors.\n \n \n \n\n\n \n Rahmani Dabbagh, S.; Rabbi, F.; Dogan, Z.; Yetisen, A.; and Tasoglu, S.\n\n\n \n\n\n\n Biomicrofluidics, 14: 61506. 12 2020.\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{article,\n    author = {Rahmani Dabbagh, Sajjad and Rabbi, Fazle and Dogan, Zafer and Yetisen, Ali and Tasoglu, Savas},\n    year = {2020},\n    month = {12},\n    pages = {61506},\n    title = {Machine learning-enabled multiplexed microfluidic sensors},\n    volume = {14},\n    journal = {Biomicrofluidics},\n    doi = {10.1063/5.0025462},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n \n A Review of Surface Haptics: Enabling Tactile Effects on Touch Surfaces.\n \n \n \n \n\n\n \n Basdogan, C.; Giraud, F.; Levesque, V.; and Choi, S.\n\n\n \n\n\n\n IEEE Transactions on Haptics, 13(3). 2020.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{Basdogan_2020,\n    title = {A Review of Surface Haptics: Enabling Tactile Effects on Touch Surfaces},\n    volume = {13},\n    issn = {2334-0134},\n    url = {http://dx.doi.org/10.1109/TOH.2020.2990712},\n    doi = {10.1109/toh.2020.2990712},\n    number = {3},\n    journal = {IEEE Transactions on Haptics},\n    publisher = {Institute of Electrical and Electronics Engineers (IEEE)},\n    author = {Basdogan, Cagatay and Giraud, Frederic and Levesque, Vincent and Choi, Seungmoon},\n    year = {2020},\n    keywords = {HCI},\n}\n\n
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\n \n\n \n \n \n \n \n Affective synthesis and animation of arm gestures from speech prosody.\n \n \n \n\n\n \n Bozkurt, E.; Yemez, Y.; and Erzin, E.\n\n\n \n\n\n\n Speech Communication. 2020.\n \n\n\n\n
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@article{bozkurt2020affective,\n    title = {Affective synthesis and animation of arm gestures from speech prosody},\n    author = {Bozkurt, Elif and Yemez, Y{\\"u}cel and Erzin, Engin},\n    journal = {Speech Communication},\n    year = {2020},\n    publisher = {North-Holland},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Automatic Vocal Tractlandmark Tracking in Rtmri Using Fully Convolutional Networks and Kalman Filter.\n \n \n \n\n\n \n Asadiabadi, S.; and Erzin, E.\n\n\n \n\n\n\n In ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 7339–7343, 2020. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{asadiabadi2020automatic,\n    title = {Automatic Vocal Tractlandmark Tracking in Rtmri Using Fully Convolutional Networks and Kalman Filter},\n    author = {Asadiabadi, Sasan and Erzin, Engin},\n    booktitle = {ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    pages = {7339--7343},\n    year = {2020},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Emotion Dependent Facial Animation from Affective Speech.\n \n \n \n\n\n \n Sadiq, R.; Asadiabadi, S.; and Erzin, E.\n\n\n \n\n\n\n In 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), pages 1-6, 2020. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{sadiq2020mmsp,\n    author = {Sadiq, Rizwan and Asadiabadi, Sasan and Erzin, Engin},\n    booktitle = {2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)},\n    title = {Emotion Dependent Facial Animation from Affective Speech},\n    year = {2020},\n    pages = {1-6},\n    doi = {10.1109/MMSP48831.2020.9287086}}
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\n \n\n \n \n \n \n \n A Diversity Combination Model Incorporating an Inward Bias for Interaural Time-Level Difference Cue Integration in Sound Lateralization.\n \n \n \n\n\n \n Mojtahedi, S.; Erzin, E.; and Ungan, P.\n\n\n \n\n\n\n Applied Sciences, 10(18): 6356. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{mojtahedi2020diversity,\n    title = {A Diversity Combination Model Incorporating an Inward Bias for Interaural Time-Level Difference Cue Integration in Sound Lateralization},\n    author = {Mojtahedi, Sina and Erzin, Engin and Ungan, Pekcan},\n    journal = {Applied Sciences},\n    volume = {10},\n    number = {18},\n    pages = {6356},\n    year = {2020},\n    publisher = {Multidisciplinary Digital Publishing Institute},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Multimodal Continuous Emotion Recognition using Deep Multi-Task Learning with Correlation Loss.\n \n \n \n\n\n \n Köprü, B.; and Erzin, E.\n\n\n \n\n\n\n arXiv preprint arXiv:2011.00876. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{kopru2020multimodal,\n    title = {Multimodal Continuous Emotion Recognition using Deep Multi-Task Learning with Correlation Loss},\n    author = {K{\\"o}pr{\\"u}, Berkay and Erzin, Engin},\n    journal = {arXiv preprint arXiv:2011.00876},\n    year = {2020},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Vocal Tract Contour Tracking in rtMRI Using Deep Temporal Regression Network.\n \n \n \n\n\n \n Asadiabadi, S.; and Erzin, E.\n\n\n \n\n\n\n IEEE/ACM Transactions on Audio, Speech, and Language Processing. 2020.\n \n\n\n\n
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@article{asadiabadi2020vocal,\n    title = {Vocal Tract Contour Tracking in rtMRI Using Deep Temporal Regression Network},\n    author = {Asadiabadi, Sasan and Erzin, Engin},\n    journal = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},\n    year = {2020},\n    publisher = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n \n BiLingUNet: Image Segmentation by Modulating Top-Down and Bottom-Up Visual Processing with Referring Expressions.\n \n \n \n \n\n\n \n Can, O. A.; Kesen, İ.; and Yuret, D.\n\n\n \n\n\n\n 2020.\n (rejected)\n\n\n\n
\n\n\n\n \n \n \"BiLingUNet:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@conference{bilingunet2020,\n    author = {Can, Ozan Arkan and Kesen, {\\.I}lker and Yuret, Deniz},\n    title = {BiLingUNet: Image Segmentation by Modulating Top-Down and Bottom-Up Visual Processing with Referring Expressions},\n    booktitle = {ECCV},\n    year = {2020},\n    url = {https://arxiv.org/abs/2003.12739},\n    keywords = {ai.ku,NLP},\n    note = {(rejected)},\n}\n\n
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\n \n\n \n \n \n \n \n \n KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media.\n \n \n \n \n\n\n \n Safaya, A.; Abdullatif, M.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 2054–2059, Barcelona (online), Dec 2020. International Committee for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"KUISAILPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{safaya-etal-2020-kuisail,\n    title = {{KUISAIL} at {S}em{E}val-2020 Task 12: {BERT}-{CNN} for Offensive Speech Identification in Social Media},\n    author = {Safaya, Ali and Abdullatif, Moutasem and Yuret, Deniz},\n    booktitle = {Proceedings of the Fourteenth Workshop on Semantic Evaluation},\n    month = {Dec},\n    year = {2020},\n    address = {Barcelona (online)},\n    publisher = {International Committee for Computational Linguistics},\n    url = {https://www.aclweb.org/anthology/2020.semeval-1.271},\n    pages = {2054--2059},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Reward Learning From Very Few Demonstrations.\n \n \n \n\n\n \n Eteke, C.; Kebüde, D.; and Akgün, B.\n\n\n \n\n\n\n IEEE Transactions on Robotics, 37(3): 893–904. 2020.\n \n\n\n\n
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@article{eteke2020reward,\n    title = {Reward Learning From Very Few Demonstrations},\n    author = {Eteke, Cem and Keb{\\"u}de, Do{\\u{g}}ancan and Akg{\\"u}n, Bar{\\i}{\\c{s}}},\n    journal = {IEEE Transactions on Robotics},\n    volume = {37},\n    number = {3},\n    pages = {893--904},\n    year = {2020},\n    publisher = {IEEE},\n    keywords = {R},\n}\n\n
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\n \n\n \n \n \n \n \n A novel haptic feature set for the classification of interactive motor behaviors in collaborative object transfer.\n \n \n \n\n\n \n Al-Saadi, Z.; Sirintuna, D.; Kucukyilmaz, A.; and Basdogan, C.\n\n\n \n\n\n\n IEEE Transactions on Haptics, 14(2): 384–395. 2020.\n \n\n\n\n
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@article{al2020novel,\n    title = {A novel haptic feature set for the classification of interactive motor behaviors in collaborative object transfer},\n    author = {Al-Saadi, Zaid and Sirintuna, Doganay and Kucukyilmaz, Ayse and Basdogan, Cagatay},\n    journal = {IEEE Transactions on Haptics},\n    volume = {14},\n    number = {2},\n    pages = {384--395},\n    year = {2020},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Effect of remote masking on tactile perception of electrovibration.\n \n \n \n\n\n \n Jamalzadeh, M.; Basdogan, C.; and Güçlü, B.\n\n\n \n\n\n\n IEEE Transactions on Haptics, 14(1): 132–142. 2020.\n \n\n\n\n
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@article{jamalzadeh2020effect,\n    title = {Effect of remote masking on tactile perception of electrovibration},\n    author = {Jamalzadeh, Milad and Basdogan, Cagatay and G{\\"u}{\\c{c}}l{\\"u}, Burak},\n    journal = {IEEE Transactions on Haptics},\n    volume = {14},\n    number = {1},\n    pages = {132--142},\n    year = {2020},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Controlling P2P-CDN live streaming services at SDN-enabled multi-access edge datacenters.\n \n \n \n\n\n \n Nacakli, S.; and Tekalp, A M.\n\n\n \n\n\n\n IEEE Transactions on Multimedia, 23: 3805–3816. 2020.\n \n\n\n\n
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@article{nacakli2020controlling,\n    title = {Controlling P2P-CDN live streaming services at SDN-enabled multi-access edge datacenters},\n    author = {Nacakli, Selin and Tekalp, A Murat},\n    journal = {IEEE Transactions on Multimedia},\n    volume = {23},\n    pages = {3805--3816},\n    year = {2020},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n SynergyChain: Blockchain-assisted adaptive cyber-physical P2P energy trading.\n \n \n \n\n\n \n Ali, F. S.; Bouachir, O.; Özkasap, Ö.; and Aloqaily, M.\n\n\n \n\n\n\n IEEE Transactions on Industrial Informatics, 17(8): 5769–5778. 2020.\n \n\n\n\n
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@article{ali2020synergychain,\n    title = {SynergyChain: Blockchain-assisted adaptive cyber-physical P2P energy trading},\n    author = {Ali, Faizan Safdar and Bouachir, Ouns and {\\"O}zkasap, {\\"O}znur and Aloqaily, Moayad},\n    journal = {IEEE Transactions on Industrial Informatics},\n    volume = {17},\n    number = {8},\n    pages = {5769--5778},\n    year = {2020},\n    publisher = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Automated extraction of socio-political events from news (AESPEN): Workshop and shared task report.\n \n \n \n\n\n \n Hürriyetoğlu, A.; Zavarella, V.; Tanev, H.; Yörük, E.; Safaya, A.; and Mutlu, O.\n\n\n \n\n\n\n arXiv preprint arXiv:2005.06070. 2020.\n \n\n\n\n
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@article{hurriyetouglu2020automated,\n    title = {Automated extraction of socio-political events from news (AESPEN): Workshop and shared task report},\n    author = {H{\\"u}rriyeto{\\u{g}}lu, Ali and Zavarella, Vanni and Tanev, Hristo and Y{\\"o}r{\\"u}k, Erdem and Safaya, Ali and Mutlu, Osman},\n    journal = {arXiv preprint arXiv:2005.06070},\n    year = {2020},\n}\n\n
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\n \n\n \n \n \n \n \n Adaptive Level Binning: A new algorithm for solving sparse triangular systems.\n \n \n \n\n\n \n Yılmaz, B.; Sipahioğrlu, B.; Ahmad, N.; and Unat, D.\n\n\n \n\n\n\n In Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, pages 188–198, 2020. \n \n\n\n\n
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@inproceedings{yilmaz2020adaptive,\n    title = {Adaptive Level Binning: A new algorithm for solving sparse triangular systems},\n    author = {Y{\\i}lmaz, Buse and Sipahio{\\u{g}}rlu, Bu{\\u{g}}rra and Ahmad, Najeeb and Unat, Didem},\n    booktitle = {Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region},\n    pages = {188--198},\n    year = {2020},\n}\n\n
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\n \n\n \n \n \n \n \n Generation of 3D human models and animations using simple sketches.\n \n \n \n\n\n \n Akman, A.; Sahillioglu, Y.; and Sezgin, T M.\n\n\n \n\n\n\n In Graphics Interface 2020, 2020. \n \n\n\n\n
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@inproceedings{akman2020generation,\n    title = {Generation of 3D human models and animations using simple sketches},\n    author = {Akman, Alican and Sahillioglu, Yusuf and Sezgin, T Metin},\n    booktitle = {Graphics Interface 2020},\n    year = {2020},\n}\n\n
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\n \n\n \n \n \n \n \n Skip graph middleware implementation.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Nayal, N.; Hamdan, S. S.; Şahin, A. U.; Özkasap, Ö.; and Küpçü, A.\n\n\n \n\n\n\n In 2020 International Symposium on Reliable Distributed Systems (SRDS), pages 335–337, 2020. IEEE\n \n\n\n\n
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@inproceedings{hassanzadeh2020skip,\n    title = {Skip graph middleware implementation},\n    author = {Hassanzadeh-Nazarabadi, Yahya and Nayal, Nazir and Hamdan, Shadi Sameh and {\\c{S}}ahin, Ali Utkan and {\\"O}zkasap, {\\"O}znur and K{\\"u}p{\\c{c}}{\\"u}, Alptekin},\n    booktitle = {2020 International Symposium on Reliable Distributed Systems (SRDS)},\n    pages = {335--337},\n    year = {2020},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Joulin: Blockchain-based p2p energy trading using smart contracts.\n \n \n \n\n\n \n Perk, B.; Bayraktaroğlu, C.; Doğu, E. D.; Ali, F. S.; and Ökasap, Ö.\n\n\n \n\n\n\n In 2020 IEEE Symposium on Computers and Communications (ISCC), pages 1–6, 2020. IEEE\n \n\n\n\n
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@inproceedings{perk2020joulin,\n    title = {Joulin: Blockchain-based p2p energy trading using smart contracts},\n    author = {Perk, Berrak and Bayraktaro{\\u{g}}lu, Can and Do{\\u{g}}u, Engin Deniz and Ali, Faizan Safdar and {\\"O}kasap, {\\"O}znur},\n    booktitle = {2020 IEEE Symposium on Computers and Communications (ISCC)},\n    pages = {1--6},\n    year = {2020},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Energy efficiency in SDDC: considering server and network utilities.\n \n \n \n\n\n \n Assefa, B. G.; Özkasap, Ö.; Kizil, I.; Aloqaily, M.; and Bouachir, O.\n\n\n \n\n\n\n In 2020 IEEE Symposium on Computers and Communications (ISCC), pages 1–6, 2020. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{assefa2020energy,\n    title = {Energy efficiency in SDDC: considering server and network utilities},\n    author = {Assefa, Beakal Gizachew and {\\"O}zkasap, {\\"O}znur and Kizil, Ipek and Aloqaily, Moayad and Bouachir, Ouns},\n    booktitle = {2020 IEEE Symposium on Computers and Communications (ISCC)},\n    pages = {1--6},\n    year = {2020},\n    organization = {IEEE},\n}\n\n
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\n \n\n \n \n \n \n \n Mutational effects on protein–protein interactions.\n \n \n \n\n\n \n Weako, J.; Gursoy, A.; and Keskin, O.\n\n\n \n\n\n\n In Protein Interactions: Computational Methods, Analysis And Applications, pages 109–143. World Scientific, 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@incollection{weako2020mutational,\n    title = {Mutational effects on protein--protein interactions},\n    author = {Weako, Jackson and Gursoy, Attila and Keskin, Ozlem},\n    booktitle = {Protein Interactions: Computational Methods, Analysis And Applications},\n    pages = {109--143},\n    year = {2020},\n    publisher = {World Scientific},\n}\n\n
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\n \n\n \n \n \n \n \n Androgen receptor-binding sites are highly mutated in prostate cancer.\n \n \n \n\n\n \n Morova, T.; McNeill, D. R; Lallous, N.; Gönen, M.; Dalal, K.; Wilson III, D. M; Gürsoy, A.; Keskin, Ö.; and Lack, N. A\n\n\n \n\n\n\n Nature communications, 11(1): 832. 2020.\n \n\n\n\n
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@article{morova2020androgen,\n    title = {Androgen receptor-binding sites are highly mutated in prostate cancer},\n    author = {Morova, Tun{\\c{c}} and McNeill, Daniel R and Lallous, Nada and G{\\"o}nen, Mehmet and Dalal, Kush and Wilson III, David M and G{\\"u}rsoy, Attila and Keskin, {\\"O}zlem and Lack, Nathan A},\n    journal = {Nature communications},\n    volume = {11},\n    number = {1},\n    pages = {832},\n    year = {2020},\n    publisher = {Nature Publishing Group UK London},\n}\n\n
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\n \n\n \n \n \n \n \n Embedding Alternative Conformations of Proteins in Protein–Protein Interaction Networks.\n \n \n \n\n\n \n Halakou, F.; Gursoy, A.; and Keskin, O.\n\n\n \n\n\n\n Protein-Protein Interaction Networks: Methods and Protocols,113–124. 2020.\n \n\n\n\n
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@article{halakou2020embedding,\n    title = {Embedding Alternative Conformations of Proteins in Protein--Protein Interaction Networks},\n    author = {Halakou, Farideh and Gursoy, Attila and Keskin, Ozlem},\n    journal = {Protein-Protein Interaction Networks: Methods and Protocols},\n    pages = {113--124},\n    year = {2020},\n    publisher = {Springer},\n}\n\n
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\n \n\n \n \n \n \n \n Special Issue on Surface Haptics.\n \n \n \n\n\n \n Basdogan, C.; Giraud, F.; Levesque, V.; and Choi, S.\n\n\n \n\n\n\n IEEE TRANSACTIONS ON HAPTICS, 13(3): 448–449. 2020.\n \n\n\n\n
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@article{basdogan2020special,\n    title = {Special Issue on Surface Haptics},\n    author = {Basdogan, Cagatay and Giraud, Frederic and Levesque, Vincent and Choi, Seungmoon},\n    journal = {IEEE TRANSACTIONS ON HAPTICS},\n    volume = {13},\n    number = {3},\n    pages = {448--449},\n    year = {2020},\n    publisher = {IEEE COMPUTER SOC 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA~…},\n}\n\n
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\n \n\n \n \n \n \n \n A variable-fractional order admittance controller for pHRI.\n \n \n \n\n\n \n Sirintuna, D.; Aydin, Y.; Caldiran, O.; Tokatli, O.; Patoglu, V.; and Basdogan, C.\n\n\n \n\n\n\n In 2020 IEEE International Conference on Robotics and Automation (ICRA), pages 10162–10168, 2020. IEEE\n \n\n\n\n
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@inproceedings{sirintuna2020variable,\n    title = {A variable-fractional order admittance controller for pHRI},\n    author = {Sirintuna, Doganay and Aydin, Yusuf and Caldiran, Ozan and Tokatli, Ozan and Patoglu, Volkan and Basdogan, Cagatay},\n    booktitle = {2020 IEEE International Conference on Robotics and Automation (ICRA)},\n    pages = {10162--10168},\n    year = {2020},\n    organization = {IEEE},\n}\n\n
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\n  \n 2019\n \n \n (35)\n \n \n
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\n \n\n \n \n \n \n \n \n Visually Grounded Language Learning for Robot Navigation.\n \n \n \n \n\n\n \n Ünal, E.; Can, O. A.; and Yemez, Y.\n\n\n \n\n\n\n In 1st International Workshop on Multimodal Understanding and Learning for Embodied Applications, of MULEA '19, pages 27–32, New York, NY, USA, 2019. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n \"VisuallyPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
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@inproceedings{10.1145/3347450.3357655,\n    author = {\\"{U}nal, Emre and Can, Ozan Arkan and Yemez, Y\\"{u}cel},\n    title = {Visually Grounded Language Learning for Robot Navigation},\n    year = {2019},\n    isbn = {9781450369183},\n    publisher = {Association for Computing Machinery},\n    address = {New York, NY, USA},\n    url = {https://doi.org/10.1145/3347450.3357655},\n    doi = {10.1145/3347450.3357655},\n    abstract = {We present an end-to-end deep learning model for robot navigation from raw visual pixel input and natural text instructions. The proposed model is an LSTM-based sequence-to-sequence neural network architecture with attention, which is trained on instruction-perception data samples collected in a synthetic environment. We conduct experiments on the SAIL dataset which we reconstruct in 3D so as to generate the 2D images associated with the data. Our experiments show that the performance of our model is on a par with state-of-the-art, despite the fact that it learns navigational language with end-to-end training from raw visual data.},\n    booktitle = {1st International Workshop on Multimodal Understanding and Learning for Embodied Applications},\n    pages = {27–32},\n    keywords = {CV,instruction following,natural language processing,robot navigation,visual grounding},\n    series = {MULEA '19},\n}\n\n
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\n We present an end-to-end deep learning model for robot navigation from raw visual pixel input and natural text instructions. The proposed model is an LSTM-based sequence-to-sequence neural network architecture with attention, which is trained on instruction-perception data samples collected in a synthetic environment. We conduct experiments on the SAIL dataset which we reconstruct in 3D so as to generate the 2D images associated with the data. Our experiments show that the performance of our model is on a par with state-of-the-art, despite the fact that it learns navigational language with end-to-end training from raw visual data.\n
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\n \n\n \n \n \n \n \n Batch Recurrent Q-Learning for Backchannel Generation Towards Engaging Agents.\n \n \n \n\n\n \n Hussain, N.; Erzin, E.; Sezgin, T. M.; and Yemez, Y.\n\n\n \n\n\n\n 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII),1-7. 2019.\n \n\n\n\n
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@article{Hussain2019BatchRQ,\n    title = {Batch Recurrent Q-Learning for Backchannel Generation Towards Engaging Agents},\n    author = {N. Hussain and E. Erzin and T. M. Sezgin and Y. Yemez},\n    journal = {2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)},\n    year = {2019},\n    pages = {1-7},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Learning to Follow Verbal Instructions with Visual Grounding.\n \n \n \n\n\n \n Ünal, E.; Can, O. A.; and Yemez, Y.\n\n\n \n\n\n\n 2019 27th Signal Processing and Communications Applications Conference (SIU),1-4. 2019.\n \n\n\n\n
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@article{nal2019LearningTF,\n    title = {Learning to Follow Verbal Instructions with Visual Grounding},\n    author = {Emre {\\"U}nal and Ozan Arkan Can and Y. Yemez},\n    journal = {2019 27th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2019},\n    pages = {1-4},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Head Nod Detection in Dyadic Conversations.\n \n \n \n\n\n \n Numanoglu, T.; Erzin, E.; Yemez, Y.; and Sezgin, M.\n\n\n \n\n\n\n 2019 27th Signal Processing and Communications Applications Conference (SIU),1-4. 2019.\n \n\n\n\n
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@article{Numanoglu2019HeadND,\n    title = {Head Nod Detection in Dyadic Conversations},\n    author = {Tuge Numanoglu and E. Erzin and Y. Yemez and M. Sezgin},\n    journal = {2019 27th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2019},\n    pages = {1-4},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Speech Driven Backchannel Generation using Deep Q-Network for Enhancing Engagement in Human-Robot Interaction.\n \n \n \n\n\n \n Hussain, N.; Erzin, E.; Sezgin, T. M.; and Yemez, Y.\n\n\n \n\n\n\n ArXiv, abs/1908.01618. 2019.\n \n\n\n\n
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@article{Hussain2019SpeechDB,\n    title = {Speech Driven Backchannel Generation using Deep Q-Network for Enhancing Engagement in Human-Robot Interaction},\n    author = {N. Hussain and E. Erzin and T. M. Sezgin and Y. Yemez},\n    journal = {ArXiv},\n    year = {2019},\n    volume = {abs/1908.01618},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Diffusion-based isometric depth correspondence.\n \n \n \n\n\n \n Küpçü, E.; and Yemez, Y.\n\n\n \n\n\n\n Comput. Vis. Image Underst., 189. 2019.\n \n\n\n\n
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@article{Kp2019DiffusionbasedID,\n    title = {Diffusion-based isometric depth correspondence},\n    author = {Emel K{\\"u}p{\\c{c}}{\\"u} and Y. Yemez},\n    journal = {Comput. Vis. Image Underst.},\n    year = {2019},\n    volume = {189},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Compressed Training Based Massive MIMO.\n \n \n \n\n\n \n Yilmaz, B. B.; and Erdogan, A. T.\n\n\n \n\n\n\n IEEE Transactions on Signal Processing, 67: 1191-1206. 2019.\n \n\n\n\n
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@article{Yilmaz2019CompressedTB,\n    title = {Compressed Training Based Massive MIMO},\n    author = {B. B. Yilmaz and A. T. Erdogan},\n    journal = {IEEE Transactions on Signal Processing},\n    year = {2019},\n    volume = {67},\n    pages = {1191-1206},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n Online Bounded Component Analysis: A Simple Recurrent Neural Network with Local Update Rule for Unsupervised Separation of Dependent and Independent Sources.\n \n \n \n\n\n \n Simsek, B.; and Erdogan, A. T.\n\n\n \n\n\n\n 2019 53rd Asilomar Conference on Signals, Systems, and Computers,1639-1643. 2019.\n \n\n\n\n
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@article{Simsek2019OnlineBC,\n    title = {Online Bounded Component Analysis: A Simple Recurrent Neural Network with Local Update Rule for Unsupervised Separation of Dependent and Independent Sources},\n    author = {Berfin Simsek and A. T. Erdogan},\n    journal = {2019 53rd Asilomar Conference on Signals, Systems, and Computers},\n    year = {2019},\n    pages = {1639-1643},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n Channel Estimation for Massive MIMO: A Semiblind Algorithm Exploiting QAM Structure.\n \n \n \n\n\n \n Yilmaz, B. B.; and Erdogan, A. T.\n\n\n \n\n\n\n 2019 53rd Asilomar Conference on Signals, Systems, and Computers,2077-2081. 2019.\n \n\n\n\n
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@article{Yilmaz2019ChannelEF,\n    title = {Channel Estimation for Massive MIMO: A Semiblind Algorithm Exploiting QAM Structure},\n    author = {B. B. Yilmaz and A. T. Erdogan},\n    journal = {2019 53rd Asilomar Conference on Signals, Systems, and Computers},\n    year = {2019},\n    pages = {2077-2081},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n SDN-enabled distributed open exchange: Dynamic QoS-path optimization in multi-operator services.\n \n \n \n\n\n \n Bagci, K.; and Tekalp, A.\n\n\n \n\n\n\n Comput. Networks, 162. 2019.\n \n\n\n\n
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@article{Bagci2019SDNenabledDO,\n    title = {SDN-enabled distributed open exchange: Dynamic QoS-path optimization in multi-operator services},\n    author = {K. Bagci and A. Tekalp},\n    journal = {Comput. Networks},\n    year = {2019},\n    volume = {162},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Effect of Architectures and Training Methods on the Performance of Learned Video Frame Prediction.\n \n \n \n\n\n \n Yilmaz, M.; and Tekalp, A.\n\n\n \n\n\n\n 2019 IEEE International Conference on Image Processing (ICIP),4210-4214. 2019.\n \n\n\n\n
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@article{Yilmaz2019EffectOA,\n    title = {Effect of Architectures and Training Methods on the Performance of Learned Video Frame Prediction},\n    author = {M. Yilmaz and A. Tekalp},\n    journal = {2019 IEEE International Conference on Image Processing (ICIP)},\n    year = {2019},\n    pages = {4210-4214},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Motion-Based Rate Adaptation in WebRTC Videoconferencing Using Scalable Video Coding.\n \n \n \n\n\n \n Bakar, G.; Kirmizioglu, R. A.; and Tekalp, A.\n\n\n \n\n\n\n IEEE Transactions on Multimedia, 21: 429-441. 2019.\n \n\n\n\n
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@article{Bakar2019MotionBasedRA,\n    title = {Motion-Based Rate Adaptation in WebRTC Videoconferencing Using Scalable Video Coding},\n    author = {G. Bakar and R. A. Kirmizioglu and A. Tekalp},\n    journal = {IEEE Transactions on Multimedia},\n    year = {2019},\n    volume = {21},\n    pages = {429-441},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Program analysis for process migration.\n \n \n \n\n\n \n Yilmaz, B.; Turimbetov, I.; and Unat, D.\n\n\n \n\n\n\n Proceedings of the 8th ACM SIGPLAN International Workshop on State Of the Art in Program Analysis. 2019.\n \n\n\n\n
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@article{Yilmaz2019ProgramAF,\n    title = {Program analysis for process migration},\n    author = {Buse Yilmaz and Ilyas Turimbetov and D. Unat},\n    journal = {Proceedings of the 8th ACM SIGPLAN International Workshop on State Of the Art in Program Analysis},\n    year = {2019},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Asynchronous AMR on Multi-GPUs.\n \n \n \n\n\n \n Farooqi, M. N.; Nguyen, T.; Zhang, W.; Almgren, A.; Shalf, J.; and Unat, D.\n\n\n \n\n\n\n In ISC Workshops, 2019. \n \n\n\n\n
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@inproceedings{Farooqi2019AsynchronousAO,\n    title = {Asynchronous AMR on Multi-GPUs},\n    author = {Muhammed Nufail Farooqi and Tan Nguyen and W. Zhang and A. Almgren and J. Shalf and D. Unat},\n    booktitle = {ISC Workshops},\n    year = {2019},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Privado: Privacy-Preserving Group-based Advertising using Multiple Independent Social Network Providers.\n \n \n \n\n\n \n Boshrooyeh, S. T.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n IACR Cryptol. ePrint Arch., 2019: 372. 2019.\n \n\n\n\n
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@article{Boshrooyeh2019PrivadoPG,\n    title = {Privado: Privacy-Preserving Group-based Advertising using Multiple Independent Social Network Providers},\n    author = {Sanaz Taheri Boshrooyeh and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    journal = {IACR Cryptol. ePrint Arch.},\n    year = {2019},\n    volume = {2019},\n    pages = {372},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n LightChain: A DHT-based Blockchain for Resource Constrained Environments.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n ArXiv, abs/1904.00375. 2019.\n \n\n\n\n
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@article{HassanzadehNazarabadi2019LightChainAD,\n    title = {LightChain: A DHT-based Blockchain for Resource Constrained Environments},\n    author = {Yahya Hassanzadeh-Nazarabadi and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    journal = {ArXiv},\n    year = {2019},\n    volume = {abs/1904.00375},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n HyMER: A Hybrid Machine Learning Framework for Energy Efficient Routing in SDN.\n \n \n \n\n\n \n Assefa, B. G.; and Özkasap, Ö.\n\n\n \n\n\n\n ArXiv, abs/1909.08074. 2019.\n \n\n\n\n
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@article{Assefa2019HyMERAH,\n    title = {HyMER: A Hybrid Machine Learning Framework for Energy Efficient Routing in SDN},\n    author = {Beakal Gizachew Assefa and {\\"O}znur {\\"O}zkasap},\n    journal = {ArXiv},\n    year = {2019},\n    volume = {abs/1909.08074},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n A survey of energy efficiency in SDN: Software-based methods and optimization models.\n \n \n \n\n\n \n Assefa, B. G.; and Özkasap, Ö.\n\n\n \n\n\n\n J. Netw. Comput. Appl., 137: 127-143. 2019.\n \n\n\n\n
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@article{Assefa2019ASO,\n    title = {A survey of energy efficiency in SDN: Software-based methods and optimization models},\n    author = {Beakal Gizachew Assefa and {\\"O}znur {\\"O}zkasap},\n    journal = {J. Netw. Comput. Appl.},\n    year = {2019},\n    volume = {137},\n    pages = {127-143},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Communication analysis and optimization of 3D front tracking method for multiphase flow simulations.\n \n \n \n\n\n \n Farooqi, M. N.; Izbassarov, D.; Muradoglu, M.; and Unat, D.\n\n\n \n\n\n\n The International Journal of High Performance Computing Applications, 33: 67 - 80. 2019.\n \n\n\n\n
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@article{Farooqi2019CommunicationAA,\n    title = {Communication analysis and optimization of 3D front tracking method for multiphase flow simulations},\n    author = {Muhammed Nufail Farooqi and D. Izbassarov and M. Muradoglu and D. Unat},\n    journal = {The International Journal of High Performance Computing Applications},\n    year = {2019},\n    volume = {33},\n    pages = {67 - 80},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Interlaced: Fully decentralized churn stabilization for Skip Graph-based DHTs.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n 2019.\n \n\n\n\n
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@misc{hassanzadehnazarabadi2019interlaced,\n    title = {Interlaced: Fully decentralized churn stabilization for Skip Graph-based DHTs},\n    author = {Yahya Hassanzadeh-Nazarabadi and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    year = {2019},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Decentralized utility- and locality-aware replication for heterogeneous DHT-based P2P cloud storage systems.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n 2019.\n \n\n\n\n
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@misc{hassanzadehnazarabadi2019decentralized,\n    title = {Decentralized utility- and locality-aware replication for heterogeneous DHT-based P2P cloud storage systems},\n    author = {Yahya Hassanzadeh-Nazarabadi and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    year = {2019},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Emotion Dependent Facial Animation from Affective Speech.\n \n \n \n\n\n \n Sadiq, R.; AsadiAbadi, S.; and Erzin, E.\n\n\n \n\n\n\n 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{sadiq2019emotion,\n    title = {Emotion Dependent Facial Animation from Affective Speech},\n    author = {Rizwan Sadiq and Sasan AsadiAbadi and Engin Erzin},\n    year = {2019},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n DeepDistance: A Multi-task Deep Regression Model for Cell Detection in Inverted Microscopy Images.\n \n \n \n\n\n \n Koyuncu, C. F.; Gunesli, G. N.; Cetin-Atalay, R.; and Gunduz-Demir, C.\n\n\n \n\n\n\n 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{koyuncu2019deepdistance,\n    title = {DeepDistance: A Multi-task Deep Regression Model for Cell Detection in Inverted Microscopy Images},\n    author = {Can Fahrettin Koyuncu and Gozde Nur Gunesli and Rengul Cetin-Atalay and Cigdem Gunduz-Demir},\n    year = {2019},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Batch Recurrent Q-Learning for Backchannel Generation Towards Engaging Agents.\n \n \n \n\n\n \n Hussain, N.; Erzin, E.; Sezgin, T M.; and Yemez, Y.\n\n\n \n\n\n\n In 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII), pages 1–7, 2019. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{hussain2019batch,\n    title = {Batch Recurrent Q-Learning for Backchannel Generation Towards Engaging Agents},\n    author = {Hussain, Nusrah and Erzin, Engin and Sezgin, T Metin and Yemez, Y{\\"u}cel},\n    booktitle = {2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)},\n    pages = {1--7},\n    year = {2019},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Speech Driven Backchannel Generation using Deep Q-Network for Enhancing Engagement in Human-Robot Interaction.\n \n \n \n\n\n \n Hussain, N.; Erzin, E.; Sezgin, T M.; and Yemez, Y.\n\n\n \n\n\n\n arXiv preprint arXiv:1908.01618. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{hussain2019speech,\n    title = {Speech Driven Backchannel Generation using Deep Q-Network for Enhancing Engagement in Human-Robot Interaction},\n    author = {Hussain, Nusrah and Erzin, Engin and Sezgin, T Metin and Yemez, Yucel},\n    journal = {arXiv preprint arXiv:1908.01618},\n    year = {2019},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n A New Interface for Affective State Estimation and Annotation from Speech.\n \n \n \n\n\n \n Fidan, U.; Tomar, D.; Özdil, P G.; and Erzin, E.\n\n\n \n\n\n\n In 2019 27th Signal Processing and Communications Applications Conference (SIU), pages 1–4, 2019. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{fidan2019new,\n    title = {A New Interface for Affective State Estimation and Annotation from Speech},\n    author = {Fidan, Umut and Tomar, Deniz and {\\"O}zdil, P Gizem and Erzin, Engin},\n    booktitle = {2019 27th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2019},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Head Nod Detection in Dyadic Conversations.\n \n \n \n\n\n \n Numanoğlu, T.; Erzin, E.; Yemezy, Y.; and Sezginy, M T.\n\n\n \n\n\n\n In 2019 27th Signal Processing and Communications Applications Conference (SIU), pages 1–4, 2019. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{numanouglu2019head,\n    title = {Head Nod Detection in Dyadic Conversations},\n    author = {Numano{\\u{g}}lu, Tu{\\u{g}}ҫe and Erzin, Engin and Yemezy, Y{\\"u}cel and Sezginy, M Tevfik},\n    booktitle = {2019 27th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2019},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Use of non-verbal vocalizations for continuous emotion recognition from speech and head motion.\n \n \n \n\n\n \n Fatima, S. N.; and Erzin, E.\n\n\n \n\n\n\n In 2019 14th IEEE Conference on Industrial Electronics and Applications (ICIEA), pages 433–437, 2019. IEEE\n \n\n\n\n
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@inproceedings{fatima2019use,\n    title = {Use of non-verbal vocalizations for continuous emotion recognition from speech and head motion},\n    author = {Fatima, Syeda Narjis and Erzin, Engin},\n    booktitle = {2019 14th IEEE Conference on Industrial Electronics and Applications (ICIEA)},\n    pages = {433--437},\n    year = {2019},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n \n Yapay Zeka.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n In Özcan, O., editor(s), Tasarım Ne Bekler. Koç Üniversitesi, Feb 2019.\n \n\n\n\n
\n\n\n\n \n \n \"YapayPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@incollection{yuret2018tasarim,\n    author = {Yuret, Deniz},\n    title = {Yapay Zeka},\n    booktitle = {Tasar{\\i}m Ne Bekler},\n    publisher = {Ko{\\c{c}} {\\"U}niversitesi},\n    editor = {O{\\u{g}}uzhan {\\"O}zcan},\n    year = {2019},\n    url = {https://tasarim.ku.edu.tr/},\n    month = {Feb},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n \n A Task Set Proposal for Automatic Event Information Collection across Multiple Countries.\n \n \n \n \n\n\n \n Hürriyetoğlu, A.; Yörük, E.; Yuret, D.; Yoltar, Ç.; Güler, B.; Duruşan, F.; and Mutlu, O.\n\n\n \n\n\n\n In ECIR (CLEF Organizers Lab Track), Germany, Apr 2019. \n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{ali2019ecir,\n    title = {A Task Set Proposal for Automatic Event Information Collection across Multiple Countries},\n    booktitle = {ECIR (CLEF Organizers Lab Track)},\n    year = {2019},\n    keywords = {ai.ku,NLP},\n    author = {H{\\"u}rriyeto{\\u{g}}lu, Ali and Y{\\"o}r{\\"u}k, Erdem and Yuret, Deniz and Yoltar, \\c{C}a\\u{g}r\\i and G\\"{u}ler, Burak and Duru\\c{s}an, F{\\i}rat and Mutlu, Osman},\n    url = {https://link.springer.com/content/pdf/10.1007%2F978-3-030-15719-7_42.pdf,/bib/hurriyetoglu/ali2019ecir/ecir2019.pdf,http://ecir2019.org/proceedings/},\n    address = {Germany},\n    month = {Apr},\n}\n\n
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\n \n\n \n \n \n \n \n Neural Network Regularization Through a Feature Space Discrimination Cost Function.\n \n \n \n\n\n \n Kayaalp, M.; Erdogan, A. T.; and Yuret, D.\n\n\n \n\n\n\n In NIPS, Vancouver, Dec 2019. \n (in preparation)\n\n\n\n
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@inproceedings{kayaalp2019,\n    author = {Kayaalp, Mert and Erdogan, Alper T. and Yuret, Deniz},\n    title = {Neural Network Regularization Through a Feature  Space Discrimination Cost Function},\n    booktitle = {NIPS},\n    year = {2019},\n    keywords = {ai.ku,NLP},\n    address = {Vancouver},\n    month = {Dec},\n    note = {(in preparation)},\n}\n\n
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\n \n\n \n \n \n \n \n Graph based dependency parsing using self attention and pre-trained transformers.\n \n \n \n\n\n \n Can, O. A.; Kirnap, O.; and Yuret, D.\n\n\n \n\n\n\n In EMNLP, Hong Kong, Nov 2019. \n (rejected)\n\n\n\n
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@inproceedings{can2019,\n    author = {Can, Ozan Arkan and Kirnap, Omer and Yuret, Deniz},\n    title = {Graph based dependency parsing using self attention and pre-trained transformers},\n    booktitle = {EMNLP},\n    year = {2019},\n    keywords = {ai.ku,NLP},\n    address = {Hong Kong},\n    month = {Nov},\n    note = {(rejected)},\n}\n\n
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\n \n\n \n \n \n \n \n \n KU_ai at MEDIQA 2019: Domain-specific Pre-training and Transfer Learning for Medical NLI.\n \n \n \n \n\n\n \n Cengiz, C.; Sert, U.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the 18th BioNLP Workshop and Shared Task, pages 427–436, Florence, Italy, Aug 2019. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"KU_aiPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{cengiz-etal-2019-ku,\n    title = {{KU}{\\_}ai at {MEDIQA} 2019: Domain-specific Pre-training and Transfer Learning for Medical {NLI}},\n    author = {Cengiz, Cemil and Sert, Ula{\\c{s}} and Yuret, Deniz},\n    booktitle = {Proceedings of the 18th BioNLP Workshop and Shared Task},\n    month = {Aug},\n    year = {2019},\n    address = {Florence, Italy},\n    publisher = {Association for Computational Linguistics},\n    url = {https://www.aclweb.org/anthology/W19-5045},\n    pages = {427--436},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n \n\n \n \n \n \n \n \n Morphological Analysis Using a Sequence Decoder.\n \n \n \n \n\n\n \n Akyürek, E.; Dayanık, E.; and Yuret, D.\n\n\n \n\n\n\n Transactions of the Association for Computational Linguistics, 7: 567–579. Sep 2019.\n \n\n\n\n
\n\n\n\n \n \n \"MorphologicalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@article{TACL1654,\n    author = {Aky{\\"u}rek, Ekin and Dayan{\\i}k, Erenay and Yuret, Deniz},\n    title = {Morphological Analysis Using a Sequence Decoder},\n    journal = {Transactions of the Association for Computational Linguistics},\n    volume = {7},\n    year = {2019},\n    issn = {2307-387X},\n    pages = {567--579},\n    keywords = {ai.ku,NLP},\n    url = {https://www.transacl.org/ojs/index.php/tacl/article/view/1654,https://arxiv.org/abs/1805.07946},\n    month = {Sep},\n}\n\n
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\n \n\n \n \n \n \n \n Decentralized utility-and locality-aware replication for heterogeneous DHT-based P2P cloud storage systems.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Ozkasap, O.\n\n\n \n\n\n\n IEEE Transactions on Parallel and Distributed Systems, 31(5): 1183–1193. 2019.\n \n\n\n\n
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@article{hassanzadeh2019decentralized,\n    title = {Decentralized utility-and locality-aware replication for heterogeneous DHT-based P2P cloud storage systems},\n    author = {Hassanzadeh-Nazarabadi, Yahya and K{\\"u}p{\\c{c}}{\\"u}, Alptekin and Ozkasap, Oznur},\n    journal = {IEEE Transactions on Parallel and Distributed Systems},\n    volume = {31},\n    number = {5},\n    pages = {1183--1193},\n    year = {2019},\n    publisher = {IEEE},\n}\n\n
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\n  \n 2018\n \n \n (50)\n \n \n
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\n \n\n \n \n \n \n \n Unsupervised Learning of Multi-Frame Optical Flow with Occlusions.\n \n \n \n\n\n \n Janai, J.; Güney, F.; Ranjan, A.; Black, M. J.; and Geiger, A.\n\n\n \n\n\n\n In ECCV, 2018. \n \n\n\n\n
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@inproceedings{Janai2018UnsupervisedLO,\n    title = {Unsupervised Learning of Multi-Frame Optical Flow with Occlusions},\n    author = {Joel Janai and Fatma G{\\"u}ney and A. Ranjan and Michael J. Black and Andreas Geiger},\n    booktitle = {ECCV},\n    year = {2018},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Multimodal prediction of head nods in dyadic conversations.\n \n \n \n\n\n \n Türker, B. B.; Sezgin, T. M.; Yemez, Y.; and Erzin, E.\n\n\n \n\n\n\n 2018 26th Signal Processing and Communications Applications Conference (SIU),1-4. 2018.\n \n\n\n\n
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@article{Trker2018MultimodalPO,\n    title = {Multimodal prediction of head nods in dyadic conversations},\n    author = {Bekir Berker T{\\"u}rker and T. M. Sezgin and Y. Yemez and E. Erzin},\n    journal = {2018 26th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2018},\n    pages = {1-4},\n    keywords = {HCI},\n}\n\n
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\n \n\n \n \n \n \n \n Audio-Visual Prediction of Head-Nod and Turn-Taking Events in Dyadic Interactions.\n \n \n \n\n\n \n Türker, B. B.; Erzin, E.; Yemez, Y.; and Sezgin, T. M.\n\n\n \n\n\n\n In INTERSPEECH, 2018. \n \n\n\n\n
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@inproceedings{Trker2018AudioVisualPO,\n    title = {Audio-Visual Prediction of Head-Nod and Turn-Taking Events in Dyadic Interactions},\n    author = {Bekir Berker T{\\"u}rker and E. Erzin and Y. Yemez and T. M. Sezgin},\n    booktitle = {INTERSPEECH},\n    year = {2018},\n    keywords = {HCI},\n}\n\n
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\n \n\n \n \n \n \n \n On the Integration of Optical Flow and Action Recognition.\n \n \n \n\n\n \n Sevilla-Lara, L.; Liao, Y.; Güney, F.; Jampani, V.; Geiger, A.; and Black, M. J.\n\n\n \n\n\n\n In GCPR, 2018. \n \n\n\n\n
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@inproceedings{SevillaLara2018OnTI,\n    title = {On the Integration of Optical Flow and Action Recognition},\n    author = {Laura Sevilla-Lara and Yiyi Liao and Fatma G{\\"u}ney and V. Jampani and A. Geiger and Michael J. Black},\n    booktitle = {GCPR},\n    year = {2018},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Multifaceted Engagement in Social Interaction with a Machine: The JOKER Project.\n \n \n \n\n\n \n Devillers, L.; Rosset, S.; Duplessis, G. D.; Bechade, L.; Yemez, Y.; Türker, B. B.; Sezgin, T. M.; Erzin, E.; Haddad, K.; Dupont, S.; Deléglise, P.; Estève, Y.; Lailler, C.; Gilmartin, E.; and Campbell, N.\n\n\n \n\n\n\n 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018),697-701. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@article{Devillers2018MultifacetedEI,\n    title = {Multifaceted Engagement in Social Interaction with a Machine: The JOKER Project},\n    author = {L. Devillers and S. Rosset and G. D. Duplessis and Lucile Bechade and Y. Yemez and Bekir Berker T{\\"u}rker and T. M. Sezgin and E. Erzin and K. Haddad and S. Dupont and P. Del{\\'e}glise and Y. Est{\\`e}ve and C. Lailler and E. Gilmartin and N. Campbell},\n    journal = {2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018)},\n    year = {2018},\n    pages = {697-701},\n    keywords = {HCI,MSP},\n}\n\n
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\n \n\n \n \n \n \n \n An Algorithmic Framework for Sparse Bounded Component Analysis.\n \n \n \n\n\n \n Babatas, E.; and Erdogan, A. T.\n\n\n \n\n\n\n IEEE Transactions on Signal Processing, 66: 5194-5205. 2018.\n \n\n\n\n
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@article{Babatas2018AnAF,\n    title = {An Algorithmic Framework for Sparse Bounded Component Analysis},\n    author = {Eren Babatas and A. T. Erdogan},\n    journal = {IEEE Transactions on Signal Processing},\n    year = {2018},\n    volume = {66},\n    pages = {5194-5205},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n Sparse Bounded Component Analysis for Convolutive Mixtures.\n \n \n \n\n\n \n Babatas, E.; and Erdogan, A. T.\n\n\n \n\n\n\n 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),2741-2745. 2018.\n \n\n\n\n
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@article{Babatas2018SparseBC,\n    title = {Sparse Bounded Component Analysis for Convolutive Mixtures},\n    author = {Eren Babatas and Alper T. Erdogan},\n    journal = {2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    year = {2018},\n    pages = {2741-2745},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n Fast multidimensional reduction and broadcast operations on GPU for machine learning.\n \n \n \n\n\n \n Dikbayir, D.; Çoban, E. B.; Kesen, I.; Yuret, D.; and Unat, D.\n\n\n \n\n\n\n Concurrency and Computation: Practice and Experience, 30. 2018.\n \n\n\n\n
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@article{Dikbayir2018FastMR,\n    title = {Fast multidimensional reduction and broadcast operations on GPU for machine learning},\n    author = {Doga Dikbayir and Enis Berk {\\c{C}}oban and Ilker Kesen and Deniz Yuret and D. Unat},\n    journal = {Concurrency and Computation: Practice and Experience},\n    year = {2018},\n    volume = {30},\n    keywords = {ML,NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Dynamic Control Plane for SDN at Scale.\n \n \n \n\n\n \n Görkemli, B.; Tatlicioglu, S.; Tekalp, A.; Civanlar, S.; and Lokman, E.\n\n\n \n\n\n\n IEEE Journal on Selected Areas in Communications, 36: 2688-2701. 2018.\n \n\n\n\n
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@article{Grkemli2018DynamicCP,\n    title = {Dynamic Control Plane for SDN at Scale},\n    author = {Burak G{\\"o}rkemli and Sinan Tatlicioglu and A. Tekalp and S. Civanlar and E. Lokman},\n    journal = {IEEE Journal on Selected Areas in Communications},\n    year = {2018},\n    volume = {36},\n    pages = {2688-2701},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Detection of Food Intake Events From Throat Microphone Recordings Using Convolutional Neural Networks.\n \n \n \n\n\n \n Turan, M.; and Erzin, E.\n\n\n \n\n\n\n 2018 IEEE International Conference on Multimedia & Expo Workshops (ICMEW),1-6. 2018.\n \n\n\n\n
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@article{Turan2018DetectionOF,\n    title = {Detection of Food Intake Events From Throat Microphone Recordings Using Convolutional Neural Networks},\n    author = {M. Turan and E. Erzin},\n    journal = {2018 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)},\n    year = {2018},\n    pages = {1-6},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Dynamic Resource Allocation by Batch Optimization for Value-Added Video Services Over SDN.\n \n \n \n\n\n \n Bagci, K.; and Tekalp, A.\n\n\n \n\n\n\n IEEE Transactions on Multimedia, 20: 3084-3096. 2018.\n \n\n\n\n
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@article{Bagci2018DynamicRA,\n    title = {Dynamic Resource Allocation by Batch Optimization for Value-Added Video Services Over SDN},\n    author = {K. Bagci and A. Tekalp},\n    journal = {IEEE Transactions on Multimedia},\n    year = {2018},\n    volume = {20},\n    pages = {3084-3096},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n On the importance of hidden bias and hidden entropy in representational efficiency of the Gaussian-Bipolar Restricted Boltzmann Machines.\n \n \n \n\n\n \n Isabekov, A.; and Erzin, E.\n\n\n \n\n\n\n Neural networks : the official journal of the International Neural Network Society, 105. 2018.\n \n\n\n\n
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@article{Isabekov2018OnTI,\n    title = {On the importance of hidden bias and hidden entropy in representational efficiency of the Gaussian-Bipolar Restricted Boltzmann Machines},\n    author = {Altynbek Isabekov and E. Erzin},\n    journal = {Neural networks : the official journal of the International Neural Network Society},\n    year = {2018},\n    volume = {105},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Multi-Party Webrtc Videoconferencing Using Scalable Vp9 Video: From Best-Effort Over-The-Top To Managed Value-Added Services.\n \n \n \n\n\n \n Kirmizioglu, R. A.; Kaya, B. C.; and Tekalp, A. M.\n\n\n \n\n\n\n 2018 IEEE International Conference on Multimedia and Expo (ICME),1-6. 2018.\n \n\n\n\n
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@article{Kirmizioglu2018MultiPartyWV,\n    title = {Multi-Party Webrtc Videoconferencing Using Scalable Vp9 Video: From Best-Effort Over-The-Top To Managed Value-Added Services},\n    author = {R. Arda Kirmizioglu and B. Can Kaya and A. Murat Tekalp},\n    journal = {2018 IEEE International Conference on Multimedia and Expo (ICME)},\n    year = {2018},\n    pages = {1-6},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Learned Compression Artifact Removal by Deep Residual Networks.\n \n \n \n\n\n \n Kirmemis, O.; Bakar, G.; and Tekalp, A.\n\n\n \n\n\n\n In CVPR Workshops, 2018. \n \n\n\n\n
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@inproceedings{Kirmemis2018LearnedCA,\n    title = {Learned Compression Artifact Removal by Deep Residual Networks},\n    author = {Ogun Kirmemis and G. Bakar and A. Tekalp},\n    booktitle = {CVPR Workshops},\n    year = {2018},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n TCP congestion avoidance for selective flows in SDN.\n \n \n \n\n\n \n Atli, A. V.; Uluderya, M. S.; Civanlar, S.; Gorkemli, B.; and Tekalp, A.\n\n\n \n\n\n\n 2018 26th Signal Processing and Communications Applications Conference (SIU),1-4. 2018.\n \n\n\n\n
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@article{Atli2018TCPCA,\n    title = {TCP congestion avoidance for selective flows in SDN},\n    author = {Ali Volkan Atli and M. S. Uluderya and S. Civanlar and B. Gorkemli and A. Tekalp},\n    journal = {2018 26th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2018},\n    pages = {1-4},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Managed P2P-assisted video services over SDN.\n \n \n \n\n\n \n Yilmaz, S.; and Tekalp, A.\n\n\n \n\n\n\n 2018 26th Signal Processing and Communications Applications Conference (SIU),1-4. 2018.\n \n\n\n\n
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@article{Yilmaz2018ManagedPV,\n    title = {Managed P2P-assisted video services over SDN},\n    author = {S. Yilmaz and A. Tekalp},\n    journal = {2018 26th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2018},\n    pages = {1-4},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Effect of Training and Test Datasets on Image Restoration and Super-Resolution by Deep Learning.\n \n \n \n\n\n \n Kirmemis, O.; and Tekalp, A.\n\n\n \n\n\n\n 2018 26th European Signal Processing Conference (EUSIPCO),514-518. 2018.\n \n\n\n\n
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@article{Kirmemis2018EffectOT,\n    title = {Effect of Training and Test Datasets on Image Restoration and Super-Resolution by Deep Learning},\n    author = {Ogun Kirmemis and A. Tekalp},\n    journal = {2018 26th European Signal Processing Conference (EUSIPCO)},\n    year = {2018},\n    pages = {514-518},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Multimodal Speech Driven Facial Shape Animation Using Deep Neural Networks.\n \n \n \n\n\n \n Asadiabadi, S.; Sadiq, R.; and Erzin, E.\n\n\n \n\n\n\n 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC),1508-1512. 2018.\n \n\n\n\n
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@article{Asadiabadi2018MultimodalSD,\n    title = {Multimodal Speech Driven Facial Shape Animation Using Deep Neural Networks},\n    author = {Sasan Asadiabadi and R. Sadiq and E. Erzin},\n    journal = {2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)},\n    year = {2018},\n    pages = {1508-1512},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Monitoring Infant's Emotional Cry in Domestic Environments Using the Capsule Network Architecture.\n \n \n \n\n\n \n Turan, M.; and Erzin, E.\n\n\n \n\n\n\n In INTERSPEECH, 2018. \n \n\n\n\n
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@inproceedings{Turan2018MonitoringIE,\n    title = {Monitoring Infant's Emotional Cry in Domestic Environments Using the Capsule Network Architecture},\n    author = {Mehmet Turan and E. Erzin},\n    booktitle = {INTERSPEECH},\n    year = {2018},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Morphological Disambiguation for Turkish.\n \n \n \n\n\n \n Hakkani-Tur, D.; Saraçlar, M.; Tur, G.; Oflazer, K.; and Yuret, D.\n\n\n \n\n\n\n In Morphological Disambiguation for Turkish, 2018. \n \n\n\n\n
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@inproceedings{HakkaniTur2018MorphologicalDF,\n    booktitle = {Morphological Disambiguation for Turkish},\n    title = {Morphological Disambiguation for Turkish},\n    author = {D. Hakkani-Tur and M. Sara{\\c{c}}lar and G. Tur and Kemal Oflazer and Deniz Yuret},\n    year = {2018},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Flow State Feedback Through Sports Wearables: A Case Study on Tennis.\n \n \n \n\n\n \n Havlucu, H.; Eskenazi, T.; Akgün, B.; Onbasli, M. C.; Coskun, A.; and Özcan, O.\n\n\n \n\n\n\n Proceedings of the 2018 Designing Interactive Systems Conference. 2018.\n \n\n\n\n
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@article{Havlucu2018FlowSF,\n    title = {Flow State Feedback Through Sports Wearables: A Case Study on Tennis},\n    author = {Hayati Havlucu and T. Eskenazi and Baris Akg{\\"u}n and M. C. Onbasli and Aykut Coskun and O{\\u{g}}uzhan {\\"O}zcan},\n    journal = {Proceedings of the 2018 Designing Interactive Systems Conference},\n    year = {2018},\n    keywords = {R},\n}\n\n
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\n \n\n \n \n \n \n \n Distributed landmark placement in P2P networks.\n \n \n \n\n\n \n Boshrooyeh, S. T.; Özkasap, Ö.; and Akgün, B.\n\n\n \n\n\n\n 2018 26th Signal Processing and Communications Applications Conference (SIU),1-4. 2018.\n \n\n\n\n
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@article{Boshrooyeh2018DistributedLP,\n    title = {Distributed landmark placement in P2P networks},\n    author = {Sanaz Taheri Boshrooyeh and {\\"O}znur {\\"O}zkasap and Baris Akg{\\"u}n},\n    journal = {2018 26th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2018},\n    pages = {1-4},\n    keywords = {R},\n}\n\n
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\n \n\n \n \n \n \n \n Communicative Cues for Reach-to-Grasp Motions: From Humans to Robots.\n \n \n \n\n\n \n Kebüde, D.; Eteke, C.; Sezgin, T. M.; and Akgün, B.\n\n\n \n\n\n\n In AAMAS, 2018. \n \n\n\n\n
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@inproceedings{Kebde2018CommunicativeCF,\n    title = {Communicative Cues for Reach-to-Grasp Motions: From Humans to Robots},\n    author = {Dogancan Keb{\\"u}de and Cem Eteke and T. M. Sezgin and Baris Akg{\\"u}n},\n    booktitle = {AAMAS},\n    year = {2018},\n    keywords = {R},\n}\n\n
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\n \n\n \n \n \n \n \n Runtime Determinacy Race Detection for OpenMP Tasks.\n \n \n \n\n\n \n Matar, H. S.; and Unat, D.\n\n\n \n\n\n\n In Euro-Par, 2018. \n \n\n\n\n
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@inproceedings{Matar2018RuntimeDR,\n    title = {Runtime Determinacy Race Detection for OpenMP Tasks},\n    author = {Hassan Salehe Matar and D. Unat},\n    booktitle = {Euro-Par},\n    year = {2018},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n BindMe: A thread binding library with advanced mapping algorithms.\n \n \n \n\n\n \n Soomro, P. N.; Sasongko, M. A.; and Unat, D.\n\n\n \n\n\n\n Concurrency and Computation: Practice and Experience, 30. 2018.\n \n\n\n\n
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@article{Soomro2018BindMeAT,\n    title = {BindMe: A thread binding library with advanced mapping algorithms},\n    author = {Pirah Noor Soomro and Muhammad Aditya Sasongko and D. Unat},\n    journal = {Concurrency and Computation: Practice and Experience},\n    year = {2018},\n    volume = {30},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n SkipVis: A skip graph visualizer.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Ekmekci, C.; Menceloglu, E.; and Özkasap, Ö.\n\n\n \n\n\n\n 2018 26th Signal Processing and Communications Applications Conference (SIU),1-4. 2018.\n \n\n\n\n
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@article{HassanzadehNazarabadi2018SkipVisAS,\n    title = {SkipVis: A skip graph visualizer},\n    author = {Yahya Hassanzadeh-Nazarabadi and C. Ekmekci and Esin Menceloglu and {\\"O}znur {\\"O}zkasap},\n    journal = {2018 26th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2018},\n    pages = {1-4},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n PPAD: Privacy Preserving Group-Based ADvertising in Online Social Networks.\n \n \n \n\n\n \n Boshrooyeh, S. T.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n 2018 IFIP Networking Conference (IFIP Networking) and Workshops,1-9. 2018.\n \n\n\n\n
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@article{Boshrooyeh2018PPADPP,\n    title = {PPAD: Privacy Preserving Group-Based ADvertising in Online Social Networks},\n    author = {Sanaz Taheri Boshrooyeh and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    journal = {2018 IFIP Networking Conference (IFIP Networking) and Workshops},\n    year = {2018},\n    pages = {1-9},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Data-driven anomaly detection in autonomous platoon.\n \n \n \n\n\n \n Ucar, S.; Ergen, S.; and Özkasap, Ö.\n\n\n \n\n\n\n 2018 26th Signal Processing and Communications Applications Conference (SIU),1-4. 2018.\n \n\n\n\n
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@article{Ucar2018DatadrivenAD,\n    title = {Data-driven anomaly detection in autonomous platoon},\n    author = {Seyhan Ucar and S. Ergen and {\\"O}znur {\\"O}zkasap},\n    journal = {2018 26th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2018},\n    pages = {1-4},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Output nondeterminism detection for programming models combining dataflow with shared memory.\n \n \n \n\n\n \n Matar, H. S.; Mutlu, E.; Tasiran, S.; and Unat, D.\n\n\n \n\n\n\n Parallel Comput., 71: 42-57. 2018.\n \n\n\n\n
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@article{Matar2018OutputND,\n    title = {Output nondeterminism detection for programming models combining dataflow with shared memory},\n    author = {Hassan Salehe Matar and Erdal Mutlu and S. Tasiran and D. Unat},\n    journal = {Parallel Comput.},\n    year = {2018},\n    volume = {71},\n    pages = {42-57},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Load Balancing for Parallel Multiphase Flow Simulation.\n \n \n \n\n\n \n Ahmad, N.; Farooqi, M. N.; and Unat, D.\n\n\n \n\n\n\n Sci. Program., 2018: 6387049:1-6387049:14. 2018.\n \n\n\n\n
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@article{Ahmad2018LoadBF,\n    title = {Load Balancing for Parallel Multiphase Flow Simulation},\n    author = {Najeeb Ahmad and Muhammed Nufail Farooqi and D. Unat},\n    journal = {Sci. Program.},\n    year = {2018},\n    volume = {2018},\n    pages = {6387049:1-6387049:14},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n IEEE 802.11p and Visible Light Hybrid Communication Based Secure Autonomous Platoon.\n \n \n \n\n\n \n Ucar, S.; Ergen, S.; and Ozkasap, O.\n\n\n \n\n\n\n IEEE Transactions on Vehicular Technology, 67: 8667-8681. 2018.\n \n\n\n\n
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@article{Ucar2018IEEE8A,\n    title = {IEEE 802.11p and Visible Light Hybrid Communication Based Secure Autonomous Platoon},\n    author = {Seyhan Ucar and S. Ergen and O. Ozkasap},\n    journal = {IEEE Transactions on Vehicular Technology},\n    year = {2018},\n    volume = {67},\n    pages = {8667-8681},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Efficient checkpointing mechanisms for primary‐backup replication on the cloud.\n \n \n \n\n\n \n Guler, B.; and Özkasap, Ö.\n\n\n \n\n\n\n Concurrency and Computation: Practice and Experience, 30. 2018.\n \n\n\n\n
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@article{Guler2018EfficientCM,\n    title = {Efficient checkpointing mechanisms for primary‐backup replication on the cloud},\n    author = {Berkin Guler and {\\"O}znur {\\"O}zkasap},\n    journal = {Concurrency and Computation: Practice and Experience},\n    year = {2018},\n    volume = {30},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Decentralized and locality aware replication method for DHT-based P2P storage systems.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n Future Gener. Comput. Syst., 84: 32-46. 2018.\n \n\n\n\n
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@article{HassanzadehNazarabadi2018DecentralizedAL,\n    title = {Decentralized and locality aware replication method for DHT-based P2P storage systems},\n    author = {Yahya Hassanzadeh-Nazarabadi and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    journal = {Future Gener. Comput. Syst.},\n    year = {2018},\n    volume = {84},\n    pages = {32-46},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Multifaceted engagement in social interaction with a machine: The joker project.\n \n \n \n\n\n \n Devillers, L.; Rosset, S.; Duplessis, G. D.; Bechade, L.; Yemez, Y.; Turker, B. B; Sezgin, M.; Erzin, E.; El Haddad, K.; Dupont, S.; and others\n\n\n \n\n\n\n In 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pages 697–701, 2018. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{devillers2018multifaceted,\n    title = {Multifaceted engagement in social interaction with a machine: The joker project},\n    author = {Devillers, Laurence and Rosset, Sophie and Duplessis, Guillaume Dubuisson and Bechade, Lucile and Yemez, Yucel and Turker, Bekir B and Sezgin, Metin and Erzin, Engin and El Haddad, Kevin and Dupont, Stephane and others},\n    booktitle = {2018 13th IEEE International Conference on Automatic Face \\& Gesture Recognition (FG 2018)},\n    pages = {697--701},\n    year = {2018},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n On the importance of hidden bias and hidden entropy in representational efficiency of the Gaussian-Bipolar Restricted Boltzmann Machines.\n \n \n \n\n\n \n Isabekov, A.; and Erzin, E.\n\n\n \n\n\n\n Neural Networks, 105: 405–418. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{isabekov2018importance,\n    title = {On the importance of hidden bias and hidden entropy in representational efficiency of the Gaussian-Bipolar Restricted Boltzmann Machines},\n    author = {Isabekov, Altynbek and Erzin, Engin},\n    journal = {Neural Networks},\n    volume = {105},\n    pages = {405--418},\n    year = {2018},\n    publisher = {Pergamon},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Audio-Visual Prediction of Head-Nod and Turn-Taking Events in Dyadic Interactions.\n \n \n \n\n\n \n Türker, B. B.; Erzin, E.; Yemez, Y.; and Sezgin, T M.\n\n\n \n\n\n\n In INTERSPEECH, pages 1741–1745, 2018. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{turker2018audio,\n    title = {Audio-Visual Prediction of Head-Nod and Turn-Taking Events in Dyadic Interactions.},\n    author = {T{\\"u}rker, Bekir Berker and Erzin, Engin and Yemez, Y{\\"u}cel and Sezgin, T Metin},\n    booktitle = {INTERSPEECH},\n    pages = {1741--1745},\n    year = {2018},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Multimodal prediction of head nods in dyadic conversations.\n \n \n \n\n\n \n Türker, B B.; Sezgin, M T.; Yemez, Y.; and Erzin, E.\n\n\n \n\n\n\n In 2018 26th Signal Processing and Communications Applications Conference (SIU), pages 1–4, 2018. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{turker2018multimodal,\n    title = {Multimodal prediction of head nods in dyadic conversations},\n    author = {T{\\"u}rker, B Berker and Sezgin, M Tevfik and Yemez, Y{\\"u}cel and Erzin, Engin},\n    booktitle = {2018 26th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2018},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Food intake detection using autoencoder-based deep neural networks.\n \n \n \n\n\n \n Turan, M. T.; and Erzin, E.\n\n\n \n\n\n\n In 2018 26th Signal Processing and Communications Applications Conference (SIU), pages 1–4, 2018. IEEE\n \n\n\n\n
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@inproceedings{turan2018food,\n    title = {Food intake detection using autoencoder-based deep neural networks},\n    author = {Turan, MA Tu{\\u{g}}tekin and Erzin, Engin},\n    booktitle = {2018 26th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2018},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Monitoring Infant's Emotional Cry in Domestic Environments Using the Capsule Network Architecture.\n \n \n \n\n\n \n Turan, M. A. T.; and Erzin, E.\n\n\n \n\n\n\n In Interspeech, pages 132–136, 2018. \n \n\n\n\n
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\n 
@inproceedings{turan2018monitoring,\n    title = {Monitoring Infant's Emotional Cry in Domestic Environments Using the Capsule Network Architecture.},\n    author = {Turan, Mehmet Ali Tugtekin and Erzin, Engin},\n    booktitle = {Interspeech},\n    pages = {132--136},\n    year = {2018},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Multimodal speech driven facial shape animation using deep neural networks.\n \n \n \n\n\n \n Asadiabadi, S.; Sadiq, R.; and Erzin, E.\n\n\n \n\n\n\n In 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pages 1508–1512, 2018. IEEE\n \n\n\n\n
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@inproceedings{asadiabadi2018multimodal,\n    title = {Multimodal speech driven facial shape animation using deep neural networks},\n    author = {Asadiabadi, Sasan and Sadiq, Rizwan and Erzin, Engin},\n    booktitle = {2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)},\n    pages = {1508--1512},\n    year = {2018},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Detection of food intake events from throat microphone recordings using convolutional neural networks.\n \n \n \n\n\n \n Turan, M. T.; and Erzin, E.\n\n\n \n\n\n\n In 2018 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), pages 1–6, 2018. IEEE\n \n\n\n\n
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@inproceedings{turan2018detection,\n    title = {Detection of food intake events from throat microphone recordings using convolutional neural networks},\n    author = {Turan, MA Tu{\\u{g}}tekin and Erzin, Engin},\n    booktitle = {2018 IEEE International Conference on Multimedia \\& Expo Workshops (ICMEW)},\n    pages = {1--6},\n    year = {2018},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n A deep learning approach for data driven vocal tract area function estimation.\n \n \n \n\n\n \n Asadiabadi, S.; and Erzin, E.\n\n\n \n\n\n\n In 2018 IEEE Spoken Language Technology Workshop (SLT), pages 167–173, 2018. IEEE\n \n\n\n\n
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@inproceedings{asadiabadi2018deep,\n    title = {A deep learning approach for data driven vocal tract area function estimation},\n    author = {Asadiabadi, Sasan and Erzin, Engin},\n    booktitle = {2018 IEEE Spoken Language Technology Workshop (SLT)},\n    pages = {167--173},\n    year = {2018},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n \n Morphological Disambiguation for Turkish.\n \n \n \n \n\n\n \n Hakkani-Tür, D. Z.; Saraçlar, M.; Tür, G.; Oflazer, K.; and Yuret, D.\n\n\n \n\n\n\n In Oflazer, K.; and Saraçlar, M., editor(s), Turkish Language Processing, of Theory and Applications of Natural Language Processing, 3, pages 53–68. Springer International Publishing, July 2018.\n \n\n\n\n
\n\n\n\n \n \n \"MorphologicalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@incollection{yuret2014mor,\n    keywords = {ai.ku,NLP},\n    editor = {Oflazer, Kemal and Sara\\c{c}lar, Murat},\n    pages = {53--68},\n    month = {July},\n    year = {2018},\n    author = {Hakkani-T\\"ur, Dilek Zeynep and Sara\\c{c}lar, Murat and T\\"ur, G\\"okhan and Oflazer, Kemal and Yuret, Deniz},\n    title = {Morphological Disambiguation for {T}urkish},\n    booktitle = {Turkish Language Processing},\n    publisher = {Springer International Publishing},\n    url = {/bib/sak/yuret2014mor/tnlp-root.pdf,http://www.springer.com/gp/book/9783319901633,https://books.google.com/books?id=D-5lDwAAQBAJ},\n    series = {Theory and Applications of Natural Language Processing},\n    chapter = {3},\n    isbn = {9783319901657},\n}\n\n
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\n \n\n \n \n \n \n \n \n Fast Multidimensional Reduction and Broadcast Operations on GPU for Machine Learning.\n \n \n \n \n\n\n \n Dikbayır, D.; Çoban, E. B.; Kesen, İ.; Yuret, D.; and Unat, D.\n\n\n \n\n\n\n Concurrency and Computation: Practice and Experience. May 2018.\n \n\n\n\n
\n\n\n\n \n \n \"FastPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{dikbayir2018,\n    author = {Dikbay{\\i}r, Do\\u{g}a and \\c{C}oban, Enis Berk and Kesen, \\.Ilker and Yuret, Deniz and Unat, Didem},\n    journal = {Concurrency and Computation: Practice and Experience},\n    year = {2018},\n    keywords = {ai.ku,NLP},\n    title = {Fast Multidimensional Reduction and Broadcast Operations on {GPU} for Machine Learning},\n    url = {https://doi.org/10.1002/cpe.4691,/bib/dikbayir/dikbayir2018/Dikbay-r_et_al-2018-Concurrency_and_Computation%253A_Practice_and_Experience.pdf},\n    month = {May},\n}\n\n
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\n \n\n \n \n \n \n \n \n On Machine Learning and Programming Languages.\n \n \n \n \n\n\n \n Innes, M.; Yuret, D.; and others\n\n\n \n\n\n\n In SysML Conference, Stanford, CA, Feb 2018. \n \n\n\n\n
\n\n\n\n \n \n \"OnPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{Innes2018,\n    title = {On Machine Learning and Programming Languages},\n    booktitle = {SysML Conference},\n    year = {2018},\n    url = {http://www.sysml.cc/doc/37.pdf,http://www.sysml.cc/},\n    keywords = {ai.ku,NLP},\n    address = {Stanford, CA},\n    month = {Feb},\n    author = {Innes, Mike and Yuret, Deniz and others},\n}\n\n
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\n \n\n \n \n \n \n \n \n A new dataset and model for learning to understand navigational instructions.\n \n \n \n \n\n\n \n Can, O. A.; and Yuret, D.\n\n\n \n\n\n\n arXiv 1805.07952 (cs.CL), Dec 2018.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@misc{can2018navi,\n    author = {Can, Ozan Arkan and Yuret, Deniz},\n    title = {A new dataset and model for learning to understand navigational instructions},\n    keywords = {ai.ku,NLP},\n    month = {Dec},\n    url = {https://arxiv.org/abs/1805.07952},\n    howpublished = {arXiv 1805.07952 (cs.CL)},\n    year = {2018},\n}\n\n
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\n \n\n \n \n \n \n \n \n Tree-Stack LSTM in Transition Based Dependency Parsing.\n \n \n \n \n\n\n \n Kırnap, Ö.; Dayanık, E.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 124–132, Brussels, Belgium, October 2018. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"Tree-StackPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{krnap-dayank-yuret:2018:K18-2,\n    author = {K{\\i}rnap, {\\"{O}}mer and Dayan{\\i}k, Erenay and Yuret, Deniz},\n    title = {Tree-Stack {LSTM} in Transition Based Dependency Parsing},\n    booktitle = {Proceedings of the {CoNLL} 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies},\n    month = {October},\n    year = {2018},\n    address = {Brussels, Belgium},\n    publisher = {Association for Computational Linguistics},\n    pages = {124--132},\n    url = {http://www.aclweb.org/anthology/K18-2012},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n \n\n \n \n \n \n \n \n SParse: Koç University Graph-Based Parsing System for the CoNLL 2018 Shared Task.\n \n \n \n \n\n\n \n Önder, B.; Gümeli, C.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 216–222, Brussels, Belgium, October 2018. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"SParse:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{nder-gmeli-yuret:2018:K18-2,\n    author = {{\\"{O}}nder, Berkay and G{\\"{u}}meli, Can and Yuret, Deniz},\n    title = {{SParse}: Ko{\\c{c}} University Graph-Based Parsing System for the CoNLL 2018 Shared Task},\n    booktitle = {Proceedings of the {CoNLL} 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies},\n    month = {October},\n    year = {2018},\n    address = {Brussels, Belgium},\n    publisher = {Association for Computational Linguistics},\n    pages = {216--222},\n    url = {http://www.aclweb.org/anthology/K18-2022},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n \n\n \n \n \n \n \n \n Towards Generalizable Place Name Recognition Systems: Analysis and Enhancement of NER Systems on English News from India.\n \n \n \n \n\n\n \n Akdemir, A.; Hürriyetoğlu, A.; Yörük, E.; Gürel, B.; Yoltar, Ç.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the 12th Workshop on Geographic Information Retrieval, of GIR'18, pages 8:1–8:10, New York, NY, USA, Nov 2018. ACM\n \n\n\n\n
\n\n\n\n \n \n \"TowardsPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{Akdemir:2018:TGP:3281354.3281363,\n    title = {Towards Generalizable Place Name Recognition Systems: Analysis and Enhancement of NER Systems on English News from India},\n    booktitle = {Proceedings of the 12th Workshop on Geographic Information Retrieval},\n    series = {GIR'18},\n    year = {2018},\n    isbn = {978-1-4503-6034-0},\n    pages = {8:1--8:10},\n    doi = {10.1145/3281354.3281363},\n    publisher = {ACM},\n    address = {New York, NY, USA},\n    keywords = {ai.ku,NLP},\n    month = {Nov},\n    author = {Akdemir, Arda and H\\"{u}rriyeto\\u{g}lu, Ali and Y\\"{o}r\\"{u}k, Erdem and G\\"{u}rel, Burak and Yoltar, \\c{C}a\\u{g}ri and Yuret, Deniz},\n    annote = {Entity Extraction. Machine Learning. Named Entity Recognition. Natural Language Processing. Place Name Recognition. location="Seattle, WA, USA". articleno="8". numpages="10". acmid="3281363".},\n    url = {http://doi.acm.org/10.1145/3281354.3281363,/bib/akdemir/GIR18/justbeforecamera-ready.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n Effect of Training and Test Datasets on Image Restoration and Super-Resolution by Deep Learning.\n \n \n \n\n\n \n Kirmemis, O.; and Tekalp, A.\n\n\n \n\n\n\n 2018 26th European Signal Processing Conference (EUSIPCO),514-518. 2018.\n \n\n\n\n
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@article{Kirmemis2018EffectOT1,\n    author = {Ogun Kirmemis and A. Tekalp},\n    title = {Effect of Training and Test Datasets on Image Restoration and Super-Resolution by Deep Learning},\n    journal = {2018 26th European Signal Processing Conference (EUSIPCO)},\n    year = {2018},\n    keywords = {MSP,Affordable tangible programming},\n    pages = {514-518},\n}\n\n
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\n  \n 2017\n \n \n (58)\n \n \n
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\n \n\n \n \n \n \n \n Semantic Segmentation of RGBD Videos with Recurrent Fully Convolutional Neural Networks.\n \n \n \n\n\n \n Yurdakul, E. E.; and Yemez, Y.\n\n\n \n\n\n\n 2017 IEEE International Conference on Computer Vision Workshops (ICCVW),367-374. 2017.\n \n\n\n\n
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@article{Yurdakul2017SemanticSO,\n    title = {Semantic Segmentation of RGBD Videos with Recurrent Fully Convolutional Neural Networks},\n    author = {Ekrem Emre Yurdakul and Y. Yemez},\n    journal = {2017 IEEE International Conference on Computer Vision Workshops (ICCVW)},\n    year = {2017},\n    pages = {367-374},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Reliable Isometric Point Correspondence from Depth.\n \n \n \n\n\n \n Küpçü, E.; and Yemez, Y.\n\n\n \n\n\n\n 2017 IEEE International Conference on Computer Vision Workshops (ICCVW),1266-1273. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{Kp2017ReliableIP,\n    title = {Reliable Isometric Point Correspondence from Depth},\n    author = {Emel K{\\"u}p{\\c{c}}{\\"u} and Y. Yemez},\n    journal = {2017 IEEE International Conference on Computer Vision Workshops (ICCVW)},\n    year = {2017},\n    pages = {1266-1273},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n RGB-D Object Recognition Using Deep Convolutional Neural Networks.\n \n \n \n\n\n \n Zia, S.; Yüksel, B.; Yuret, D.; and Yemez, Y.\n\n\n \n\n\n\n 2017 IEEE International Conference on Computer Vision Workshops (ICCVW),887-894. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@article{Zia2017RGBDOR,\n    title = {RGB-D Object Recognition Using Deep Convolutional Neural Networks},\n    author = {Saman Zia and B. Y{\\"u}ksel and Deniz Yuret and Y. Yemez},\n    journal = {2017 IEEE International Conference on Computer Vision Workshops (ICCVW)},\n    year = {2017},\n    pages = {887-894},\n    keywords = {CV,NLP},\n}\n\n
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\n \n\n \n \n \n \n \n The JESTKOD database: an affective multimodal database of dyadic interactions.\n \n \n \n\n\n \n Bozkurt, E.; Khaki, H.; Keçeci, S.; Turker, B. B.; Yemez, Y.; and Erzin, E.\n\n\n \n\n\n\n Language Resources and Evaluation, 51: 857-872. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{Bozkurt2017TheJD,\n    title = {The JESTKOD database: an affective multimodal database of dyadic interactions},\n    author = {E. Bozkurt and H. Khaki and Sinan Ke{\\c{c}}eci and B. B. Turker and Y. Yemez and E. Erzin},\n    journal = {Language Resources and Evaluation},\n    year = {2017},\n    volume = {51},\n    pages = {857-872},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Slow Flow: Exploiting High-Speed Cameras for Accurate and Diverse Optical Flow Reference Data.\n \n \n \n\n\n \n Janai, J.; Güney, F.; Wulff, J.; Black, M. J.; and Geiger, A.\n\n\n \n\n\n\n 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),1406-1416. 2017.\n \n\n\n\n
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@article{Janai2017SlowFE,\n    title = {Slow Flow: Exploiting High-Speed Cameras for Accurate and Diverse Optical Flow Reference Data},\n    author = {Joel Janai and Fatma G{\\"u}ney and J. Wulff and Michael J. Black and Andreas Geiger},\n    journal = {2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},\n    year = {2017},\n    pages = {1406-1416},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Audio-Facial Laughter Detection in Naturalistic Dyadic Conversations.\n \n \n \n\n\n \n Turker, B. B.; Yemez, Y.; Sezgin, T. M.; and Erzin, E.\n\n\n \n\n\n\n IEEE Transactions on Affective Computing, 8: 534-545. 2017.\n \n\n\n\n
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@article{Turker2017AudioFacialLD,\n    title = {Audio-Facial Laughter Detection in Naturalistic Dyadic Conversations},\n    author = {B. B. Turker and Y. Yemez and T. M. Sezgin and E. Erzin},\n    journal = {IEEE Transactions on Affective Computing},\n    year = {2017},\n    volume = {8},\n    pages = {534-545},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Analysis of Engagement and User Experience with a Laughter Responsive Social Robot.\n \n \n \n\n\n \n Türker, B. B.; Buçinca, Z.; Erzin, E.; Yemez, Y.; and Sezgin, T. M.\n\n\n \n\n\n\n In INTERSPEECH, 2017. \n \n\n\n\n
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@inproceedings{Trker2017AnalysisOE,\n    title = {Analysis of Engagement and User Experience with a Laughter Responsive Social Robot},\n    author = {Bekir Berker T{\\"u}rker and Zana Bu{\\c{c}}inca and E. Erzin and Y. Yemez and T. M. Sezgin},\n    booktitle = {INTERSPEECH},\n    year = {2017},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Androgen receptor binding sites are highly mutated in prostate cancer.\n \n \n \n\n\n \n Morova, T.; Gönen, M.; Gursoy, A.; Keskin, Ö.; and Lack, N. A.\n\n\n \n\n\n\n bioRxiv. 2017.\n \n\n\n\n
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@article{Morova2017AndrogenRB,\n    title = {Androgen receptor binding sites are highly mutated in prostate cancer},\n    author = {Tun{\\c{c}} Morova and M. G{\\"o}nen and A. Gursoy and {\\"O}zlem Keskin and Nathan A. Lack},\n    journal = {bioRxiv},\n    year = {2017},\n    keywords = {CBM},\n}\n\n
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\n \n\n \n \n \n \n \n Characterizing user behavior for speech and sketch-based video retrieval interfaces.\n \n \n \n\n\n \n Altiok, O. C.; and Sezgin, T. M.\n\n\n \n\n\n\n In CAe@Expressive, 2017. \n \n\n\n\n
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@inproceedings{Altiok2017CharacterizingUB,\n    title = {Characterizing user behavior for speech and sketch-based video retrieval interfaces},\n    author = {Ozan Can Altiok and T. M. Sezgin},\n    booktitle = {CAe@Expressive},\n    year = {2017},\n    keywords = {HCI},\n}\n\n
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\n \n\n \n \n \n \n \n Visualization Literacy at Elementary School.\n \n \n \n\n\n \n Alper, B.; Riche, N.; Chevalier, F.; Boy, J.; and Sezgin, T. M.\n\n\n \n\n\n\n Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. 2017.\n \n\n\n\n
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@article{Alper2017VisualizationLA,\n    title = {Visualization Literacy at Elementary School},\n    author = {B. Alper and N. Riche and F. Chevalier and Jeremy Boy and T. M. Sezgin},\n    journal = {Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems},\n    year = {2017},\n    keywords = {HCI},\n}\n\n
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\n \n\n \n \n \n \n \n Stationary Point Characterization for a Class of BCA Algorithms.\n \n \n \n\n\n \n Inan, H. A.; Erdogan, A. T.; and Cruces, S.\n\n\n \n\n\n\n IEEE Transactions on Signal Processing, 65: 5437-5452. 2017.\n \n\n\n\n
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@article{Inan2017StationaryPC,\n    title = {Stationary Point Characterization for a Class of BCA Algorithms},\n    author = {Huseyin A. Inan and Alper T. Erdogan and S. Cruces},\n    journal = {IEEE Transactions on Signal Processing},\n    year = {2017},\n    volume = {65},\n    pages = {5437-5452},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n Single carrier frequency domain compressed training adaptive equalization.\n \n \n \n\n\n \n Yilmaz, B. B.; and Erdogan, A. T.\n\n\n \n\n\n\n 2017 51st Asilomar Conference on Signals, Systems, and Computers,1110-1114. 2017.\n \n\n\n\n
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@article{Yilmaz2017SingleCF,\n    title = {Single carrier frequency domain compressed training adaptive equalization},\n    author = {B. B. Yilmaz and A. T. Erdogan},\n    journal = {2017 51st Asilomar Conference on Signals, Systems, and Computers},\n    year = {2017},\n    pages = {1110-1114},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n Compressed Training Adaptive Equalization: Algorithms and Analysis.\n \n \n \n\n\n \n Yilmaz, B. B.; and Erdogan, A. T.\n\n\n \n\n\n\n IEEE Transactions on Communications, 65: 3907-3921. 2017.\n \n\n\n\n
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@article{Yilmaz2017CompressedTA,\n    title = {Compressed Training Adaptive Equalization: Algorithms and Analysis},\n    author = {B. B. Yilmaz and A. T. Erdogan},\n    journal = {IEEE Transactions on Communications},\n    year = {2017},\n    volume = {65},\n    pages = {3907-3921},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n Motion-Based Adaptive Streaming in WebRTC Using Spatio-Temporal Scalable VP9 Video Coding.\n \n \n \n\n\n \n Bakar, G.; Kirmizioglu, R. A.; and Tekalp, A.\n\n\n \n\n\n\n GLOBECOM 2017 - 2017 IEEE Global Communications Conference,1-6. 2017.\n \n\n\n\n
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@article{Bakar2017MotionBasedAS,\n    title = {Motion-Based Adaptive Streaming in WebRTC Using Spatio-Temporal Scalable VP9 Video Coding},\n    author = {G. Bakar and R. A. Kirmizioglu and A. Tekalp},\n    journal = {GLOBECOM 2017 - 2017 IEEE Global Communications Conference},\n    year = {2017},\n    pages = {1-6},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Distributed-collaborative managed dash video services.\n \n \n \n\n\n \n Sahin, K. E.; Bagci, K.; and Tekalp, A.\n\n\n \n\n\n\n 2017 13th International Conference on Network and Service Management (CNSM),1-5. 2017.\n \n\n\n\n
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@article{Sahin2017DistributedcollaborativeMD,\n    title = {Distributed-collaborative managed dash video services},\n    author = {Kemal E. Sahin and K. Bagci and A. Tekalp},\n    journal = {2017 13th International Conference on Network and Service Management (CNSM)},\n    year = {2017},\n    pages = {1-5},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Empirical Mode Decomposition of Throat Microphone Recordings for Intake Classification.\n \n \n \n\n\n \n Turan, M.; and Erzin, E.\n\n\n \n\n\n\n Proceedings of the 2nd International Workshop on Multimedia for Personal Health and Health Care. 2017.\n \n\n\n\n
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@article{Turan2017EmpiricalMD,\n    title = {Empirical Mode Decomposition of Throat Microphone Recordings for Intake Classification},\n    author = {M. Turan and E. Erzin},\n    journal = {Proceedings of the 2nd International Workshop on Multimedia for Personal Health and Health Care},\n    year = {2017},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Compete or Collaborate: Architectures for Collaborative DASH Video Over Future Networks.\n \n \n \n\n\n \n Bagci, K.; Sahin, K. E.; and Tekalp, A.\n\n\n \n\n\n\n IEEE Transactions on Multimedia, 19: 2152-2165. 2017.\n \n\n\n\n
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@article{Bagci2017CompeteOC,\n    title = {Compete or Collaborate: Architectures for Collaborative DASH Video Over Future Networks},\n    author = {K. Bagci and Kemal E. Sahin and A. Tekalp},\n    journal = {IEEE Transactions on Multimedia},\n    year = {2017},\n    volume = {19},\n    pages = {2152-2165},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Adaptive Multiview Video Delivery Using Hybrid Networking.\n \n \n \n\n\n \n Ekmekcioglu, E.; Gurler, C. G.; Kondoz, A.; and Tekalp, A.\n\n\n \n\n\n\n IEEE Transactions on Circuits and Systems for Video Technology, 27: 1313-1325. 2017.\n \n\n\n\n
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@article{Ekmekcioglu2017AdaptiveMV,\n    title = {Adaptive Multiview Video Delivery Using Hybrid Networking},\n    author = {E. Ekmekcioglu and C. G. Gurler and A. Kondoz and A. Tekalp},\n    journal = {IEEE Transactions on Circuits and Systems for Video Technology},\n    year = {2017},\n    volume = {27},\n    pages = {1313-1325},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Emerging 3-D Imaging and Display Technologies.\n \n \n \n\n\n \n Javidi, B.; and Tekalp, A.\n\n\n \n\n\n\n Proc. IEEE, 105: 786-788. 2017.\n \n\n\n\n
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@article{Javidi2017Emerging3I,\n    title = {Emerging 3-D Imaging and Display Technologies},\n    author = {B. Javidi and A. Tekalp},\n    journal = {Proc. IEEE},\n    year = {2017},\n    volume = {105},\n    pages = {786-788},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Virtualized cloud video services.\n \n \n \n\n\n \n Yilmaz, S.; Sahin, K. E.; Bagci, K.; and Tekalp, A.\n\n\n \n\n\n\n 2017 25th Signal Processing and Communications Applications Conference (SIU),1-4. 2017.\n \n\n\n\n
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@article{Yilmaz2017VirtualizedCV,\n    title = {Virtualized cloud video services},\n    author = {S. Yilmaz and Kemal E. Sahin and K. Bagci and A. Tekalp},\n    journal = {2017 25th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2017},\n    pages = {1-4},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Vocal Tract Airway Tissue Boundary Tracking for rtMRI Using Shape and Appearance Priors.\n \n \n \n\n\n \n Asadiabadi, S.; and Erzin, E.\n\n\n \n\n\n\n In INTERSPEECH, 2017. \n \n\n\n\n
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@inproceedings{Asadiabadi2017VocalTA,\n    title = {Vocal Tract Airway Tissue Boundary Tracking for rtMRI Using Shape and Appearance Priors},\n    author = {Sasan Asadiabadi and E. Erzin},\n    booktitle = {INTERSPEECH},\n    year = {2017},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Use of affect based interaction classification for continuous emotion tracking.\n \n \n \n\n\n \n Khaki, H.; and Erzin, E.\n\n\n \n\n\n\n 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),2881-2885. 2017.\n \n\n\n\n
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@article{Khaki2017UseOA,\n    title = {Use of affect based interaction classification for continuous emotion tracking},\n    author = {H. Khaki and E. Erzin},\n    journal = {2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    year = {2017},\n    pages = {2881-2885},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Speech features for telemonitoring of Parkinson's disease symptoms.\n \n \n \n\n\n \n Ramezani, H.; Khaki, H.; Erzin, E.; and Akan, Ö. B.\n\n\n \n\n\n\n 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC),3801-3805. 2017.\n \n\n\n\n
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@article{Ramezani2017SpeechFF,\n    title = {Speech features for telemonitoring of Parkinson's disease symptoms},\n    author = {Hamideh Ramezani and H. Khaki and E. Erzin and {\\"O}zg{\\"u}r B. Akan},\n    journal = {2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},\n    year = {2017},\n    pages = {3801-3805},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Cross-Subject Continuous Emotion Recognition Using Speech and Body Motion in Dyadic Interactions.\n \n \n \n\n\n \n Fatima, S. N.; and Erzin, E.\n\n\n \n\n\n\n In INTERSPEECH, 2017. \n \n\n\n\n
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@inproceedings{Fatima2017CrossSubjectCE,\n    title = {Cross-Subject Continuous Emotion Recognition Using Speech and Body Motion in Dyadic Interactions},\n    author = {Syeda Narjis Fatima and E. Erzin},\n    booktitle = {INTERSPEECH},\n    year = {2017},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Affect recognition from lip articulations.\n \n \n \n\n\n \n Sadiq, R.; and Erzin, E.\n\n\n \n\n\n\n 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),2432-2436. 2017.\n \n\n\n\n
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@article{Sadiq2017AffectRF,\n    title = {Affect recognition from lip articulations},\n    author = {R. Sadiq and E. Erzin},\n    journal = {2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    year = {2017},\n    pages = {2432-2436},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Relational Symbol Grounding through Affordance Learning: An Overview of the ReGround Project.\n \n \n \n\n\n \n Antanas, L.; Davis, J.; Raedt, L. D.; Loutfi, A.; Persson, A.; Saffiotti, A.; Yuret, D.; Can, O. A.; Unal, E.; and Martires, P. Z. D.\n\n\n \n\n\n\n In Relational Symbol Grounding through Affordance Learning: An Overview of the ReGround Project, 2017. \n \n\n\n\n
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@inproceedings{Antanas2017RelationalSG,\n    booktitle = {Relational Symbol Grounding through Affordance Learning: An Overview of the ReGround Project},\n    title = {Relational Symbol Grounding through Affordance Learning: An Overview of the ReGround Project},\n    author = {Laura Antanas and J. Davis and L. D. Raedt and A. Loutfi and A. Persson and A. Saffiotti and Deniz Yuret and Ozan Arkan Can and E. Unal and Pedro Zuidberg Dos Martires},\n    year = {2017},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Parsing with Context Embeddings.\n \n \n \n\n\n \n Kirnap, Ö.; Önder, B. F.; and Yuret, D.\n\n\n \n\n\n\n In CoNLL Shared Task, 2017. \n \n\n\n\n
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@inproceedings{Kirnap2017ParsingWC,\n    title = {Parsing with Context Embeddings},\n    author = {{\\"O}mer Kirnap and Berkay Furkan {\\"O}nder and Deniz Yuret},\n    booktitle = {CoNLL Shared Task},\n    year = {2017},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Multidimensional Broadcast Operation on the GPU.\n \n \n \n\n\n \n Çoban, E. B.; and Yüret, D.\n\n\n \n\n\n\n In Multidimensional Broadcast Operation on the GPU, 2017. \n \n\n\n\n
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@inproceedings{oban2017MultidimensionalBO,\n    booktitle = {Multidimensional Broadcast Operation on the GPU},\n    title = {Multidimensional Broadcast Operation on the GPU},\n    author = {Enis Berk {\\c{C}}oban and Deniz Y{\\"u}ret},\n    year = {2017},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Data-driven abnormal behavior detection for autonomous platoon.\n \n \n \n\n\n \n Ucar, S.; Ergen, S.; and Özkasap, Ö.\n\n\n \n\n\n\n 2017 IEEE Vehicular Networking Conference (VNC),69-72. 2017.\n \n\n\n\n
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@article{Ucar2017DatadrivenAB,\n    title = {Data-driven abnormal behavior detection for autonomous platoon},\n    author = {Seyhan Ucar and S. Ergen and {\\"O}znur {\\"O}zkasap},\n    journal = {2017 IEEE Vehicular Networking Conference (VNC)},\n    year = {2017},\n    pages = {69-72},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Compressed incremental checkpointing for efficient replicated key-value stores.\n \n \n \n\n\n \n Guler, B.; and Özkasap, Ö.\n\n\n \n\n\n\n 2017 IEEE Symposium on Computers and Communications (ISCC),76-81. 2017.\n \n\n\n\n
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@article{Guler2017CompressedIC,\n    title = {Compressed incremental checkpointing for efficient replicated key-value stores},\n    author = {Berkin Guler and {\\"O}znur {\\"O}zkasap},\n    journal = {2017 IEEE Symposium on Computers and Communications (ISCC)},\n    year = {2017},\n    pages = {76-81},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Analysis of checkpointing algorithms for primary-backup replication.\n \n \n \n\n\n \n Guler, B.; and Özkasap, Ö.\n\n\n \n\n\n\n 2017 IEEE Symposium on Computers and Communications (ISCC),64-69. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Guler2017AnalysisOC,\n    title = {Analysis of checkpointing algorithms for primary-backup replication},\n    author = {Berkin Guler and {\\"O}znur {\\"O}zkasap},\n    journal = {2017 IEEE Symposium on Computers and Communications (ISCC)},\n    year = {2017},\n    pages = {64-69},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Visible light communication assisted safety message dissemination in multiplatoon.\n \n \n \n\n\n \n Ucar, S.; Ergen, S.; and Özkasap, Ö.\n\n\n \n\n\n\n 2017 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom),1-5. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Ucar2017VisibleLC,\n    title = {Visible light communication assisted safety message dissemination in multiplatoon},\n    author = {Seyhan Ucar and S. Ergen and {\\"O}znur {\\"O}zkasap},\n    journal = {2017 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)},\n    year = {2017},\n    pages = {1-5},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Link utility and traffic aware energy saving in software defined networks.\n \n \n \n\n\n \n Assefa, B. G.; and Özkasap, Ö.\n\n\n \n\n\n\n 2017 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom),1-5. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Assefa2017LinkUA,\n    title = {Link utility and traffic aware energy saving in software defined networks},\n    author = {Beakal Gizachew Assefa and {\\"O}znur {\\"O}zkasap},\n    journal = {2017 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)},\n    year = {2017},\n    pages = {1-5},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n ELATS: Energy and locality aware aggregation tree for skip graph.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; and Özkasap, Ö.\n\n\n \n\n\n\n 2017 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom),1-5. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{HassanzadehNazarabadi2017ELATSEA,\n    title = {ELATS: Energy and locality aware aggregation tree for skip graph},\n    author = {Yahya Hassanzadeh-Nazarabadi and {\\"O}znur {\\"O}zkasap},\n    journal = {2017 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)},\n    year = {2017},\n    pages = {1-5},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Security vulnerabilities of autonomous platoons.\n \n \n \n\n\n \n Ucar, S.; Ergen, S.; and Özkasap, Ö.\n\n\n \n\n\n\n 2017 25th Signal Processing and Communications Applications Conference (SIU),1-4. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Ucar2017SecurityVO,\n    title = {Security vulnerabilities of autonomous platoons},\n    author = {Seyhan Ucar and S. Ergen and {\\"O}znur {\\"O}zkasap},\n    journal = {2017 25th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2017},\n    pages = {1-4},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Efficient incremental checkpoint algorithm for primary-backup replication.\n \n \n \n\n\n \n Guler, B.; and Özkasap, Ö.\n\n\n \n\n\n\n 2017 25th Signal Processing and Communications Applications Conference (SIU),1-4. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Guler2017EfficientIC,\n    title = {Efficient incremental checkpoint algorithm for primary-backup replication},\n    author = {Berkin Guler and {\\"O}znur {\\"O}zkasap},\n    journal = {2017 25th Signal Processing and Communications Applications Conference (SIU)},\n    year = {2017},\n    pages = {1-4},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Research issues for privacy and security of electronic health services.\n \n \n \n\n\n \n Yüksel, B.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n Future Gener. Comput. Syst., 68: 1-13. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Yksel2017ResearchIF,\n    title = {Research issues for privacy and security of electronic health services},\n    author = {B. Y{\\"u}ksel and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    journal = {Future Gener. Comput. Syst.},\n    year = {2017},\n    volume = {68},\n    pages = {1-13},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Overlapping Data Transfers with Computation on GPU with Tiles.\n \n \n \n\n\n \n Bastem, B.; Unat, D.; Zhang, W.; Almgren, A.; and Shalf, J.\n\n\n \n\n\n\n 2017 46th International Conference on Parallel Processing (ICPP),171-180. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Bastem2017OverlappingDT,\n    title = {Overlapping Data Transfers with Computation on GPU with Tiles},\n    author = {Burak Bastem and D. Unat and W. Zhang and A. Almgren and J. Shalf},\n    journal = {2017 46th International Conference on Parallel Processing (ICPP)},\n    year = {2017},\n    pages = {171-180},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Object Placement for High Bandwidth Memory Augmented with High Capacity Memory.\n \n \n \n\n\n \n Laghari, M.; and Unat, D.\n\n\n \n\n\n\n 2017 29th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD),129-136. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Laghari2017ObjectPF,\n    title = {Object Placement for High Bandwidth Memory Augmented with High Capacity Memory},\n    author = {Mohammad Laghari and D. Unat},\n    journal = {2017 29th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)},\n    year = {2017},\n    pages = {129-136},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n \n Androgen receptor binding sites are highly mutated in prostate cancer.\n \n \n \n \n\n\n \n Morova, T.; Gönen, M.; Gursoy, A.; Keskin, Ö.; and Lack, N. A.\n\n\n \n\n\n\n bioRxiv. 2017.\n \n\n\n\n
\n\n\n\n \n \n \"AndrogenPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n  \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{Morova225433,\n    author = {Morova, Tun{\\c c} and G{\\"o}nen, Mehmet and Gursoy, Attila and Keskin, {\\"O}zlem and Lack, Nathan A.},\n    title = {Androgen receptor binding sites are highly mutated in prostate cancer},\n    year = {2017},\n    doi = {10.1101/225433},\n    publisher = {Cold Spring Harbor Laboratory},\n    abstract = {Androgen receptor (AR) signalling is essential to nearly all prostate cancer cells. Any alterations to AR-mediated transcription can have a profound effect on prostate carcinogenesis and tumour growth. While the AR protein has been extensively studied, little is know about mutations to the non-coding regions where AR binds to DNA. Using clinical whole genome sequencing, we demonstrate that AR binding sites have a dramatically increased rate of mutations that is greater than any other transcription factor and specific to only prostate cancer. Demonstrating this may be common to lineage-specific transcription factors, estrogen receptor binding sites had an elevated rate of mutations in breast cancer. Based on the mutations observed at the binding site of AR and other related transcription factors, we proposed that AR occupancy impairs access of base excision repair enzymes to endogenous DNA damage. Overall, this work demonstrates that non-coding AR binding sites are frequently mutated in prostate cancer and may potentially act as driver mutations.},\n    url = {https://www.biorxiv.org/content/early/2017/11/27/225433},\n    journal = {bioRxiv},\n    keywords = {CBM},\n}\n\n
\n
\n\n\n
\n Androgen receptor (AR) signalling is essential to nearly all prostate cancer cells. Any alterations to AR-mediated transcription can have a profound effect on prostate carcinogenesis and tumour growth. While the AR protein has been extensively studied, little is know about mutations to the non-coding regions where AR binds to DNA. Using clinical whole genome sequencing, we demonstrate that AR binding sites have a dramatically increased rate of mutations that is greater than any other transcription factor and specific to only prostate cancer. Demonstrating this may be common to lineage-specific transcription factors, estrogen receptor binding sites had an elevated rate of mutations in breast cancer. Based on the mutations observed at the binding site of AR and other related transcription factors, we proposed that AR occupancy impairs access of base excision repair enzymes to endogenous DNA damage. Overall, this work demonstrates that non-coding AR binding sites are frequently mutated in prostate cancer and may potentially act as driver mutations.\n
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\n \n\n \n \n \n \n \n The JESTKOD database: an affective multimodal database of dyadic interactions.\n \n \n \n\n\n \n Bozkurt, E.; Khaki, H.; Keçeci, S.; Türker, B B.; Yemez, Y.; and Erzin, E.\n\n\n \n\n\n\n Language Resources and Evaluation, 51(3): 857–872. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{bozkurt2017jestkod,\n    title = {The JESTKOD database: an affective multimodal database of dyadic interactions},\n    author = {Bozkurt, Elif and Khaki, Hossein and Ke{\\c{c}}eci, Sinan and T{\\"u}rker, B Berker and Yemez, Y{\\"u}cel and Erzin, Engin},\n    journal = {Language Resources and Evaluation},\n    volume = {51},\n    number = {3},\n    pages = {857--872},\n    year = {2017},\n    publisher = {Springer Netherlands},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Use of affect based interaction classification for continuous emotion tracking.\n \n \n \n\n\n \n Khaki, H.; and Erzin, E.\n\n\n \n\n\n\n In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 2881–2885, 2017. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{khaki2017use,\n    title = {Use of affect based interaction classification for continuous emotion tracking},\n    author = {Khaki, Hossein and Erzin, Engin},\n    booktitle = {2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    pages = {2881--2885},\n    year = {2017},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Affect recognition from lip articulations.\n \n \n \n\n\n \n Sadiq, R.; and Erzin, E.\n\n\n \n\n\n\n In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 2432–2436, 2017. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{sadiq2017affect,\n    title = {Affect recognition from lip articulations},\n    author = {Sadiq, Rizwan and Erzin, Engin},\n    booktitle = {2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    pages = {2432--2436},\n    year = {2017},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Classification of ingestion sounds using Hilbert-huang transform.\n \n \n \n\n\n \n Turan, M. T.; and Erzin, E.\n\n\n \n\n\n\n In 2017 25th Signal Processing and Communications Applications Conference (SIU), pages 1–4, 2017. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{turan2017classification,\n    title = {Classification of ingestion sounds using Hilbert-huang transform},\n    author = {Turan, MA Tuggtekin and Erzin, Engin},\n    booktitle = {2017 25th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2017},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Real-time audiovisual laughter detection.\n \n \n \n\n\n \n Türker, B B.; Buçinca, Z.; Sezgin, M T.; Yemez, Y.; and Erzin, E.\n\n\n \n\n\n\n In 2017 25th Signal Processing and Communications Applications Conference (SIU), pages 1–4, 2017. IEEE\n \n\n\n\n
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@inproceedings{turker2017real,\n    title = {Real-time audiovisual laughter detection},\n    author = {T{\\"u}rker, B Berker and Bu{\\c{c}}inca, Zana and Sezgin, M Tevfik and Yemez, Y{\\"u}cel and Erzin, Engin},\n    booktitle = {2017 25th Signal Processing and Communications Applications Conference (SIU)},\n    pages = {1--4},\n    year = {2017},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Analysis of Engagement and User Experience with a Laughter Responsive Social Robot.\n \n \n \n\n\n \n Türker, B. B.; Buçinca, Z.; Erzin, E.; Yemez, Y.; and Sezgin, T M.\n\n\n \n\n\n\n In Interspeech, pages 844–848, 2017. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{turker2017analysis,\n    title = {Analysis of Engagement and User Experience with a Laughter Responsive Social Robot.},\n    author = {T{\\"u}rker, Bekir Berker and Bu{\\c{c}}inca, Zana and Erzin, Engin and Yemez, Y{\\"u}cel and Sezgin, T Metin},\n    booktitle = {Interspeech},\n    pages = {844--848},\n    year = {2017},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Vocal Tract Airway Tissue Boundary Tracking for rtMRI Using Shape and Appearance Priors.\n \n \n \n\n\n \n Asadiabadi, S.; and Erzin, E.\n\n\n \n\n\n\n In Interspeech, pages 636–640, 2017. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{asadiabadi2017vocal,\n    title = {Vocal Tract Airway Tissue Boundary Tracking for rtMRI Using Shape and Appearance Priors.},\n    author = {Asadiabadi, Sasan and Erzin, Engin},\n    booktitle = {Interspeech},\n    pages = {636--640},\n    year = {2017},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Cross-Subject Continuous Emotion Recognition Using Speech and Body Motion in Dyadic Interactions.\n \n \n \n\n\n \n Fatima, S. N.; and Erzin, E.\n\n\n \n\n\n\n In INTERSPEECH, pages 1731–1735, 2017. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{fatima2017cross,\n    title = {Cross-Subject Continuous Emotion Recognition Using Speech and Body Motion in Dyadic Interactions.},\n    author = {Fatima, Syeda Narjis and Erzin, Engin},\n    booktitle = {INTERSPEECH},\n    pages = {1731--1735},\n    year = {2017},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Speech features for telemonitoring of Parkinson's disease symptoms.\n \n \n \n\n\n \n Ramezani, H.; Khaki, H.; Erzin, E.; and Akan, O. B\n\n\n \n\n\n\n In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 3801–3805, 2017. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@inproceedings{ramezani2017speech,\n    title = {Speech features for telemonitoring of Parkinson's disease symptoms},\n    author = {Ramezani, Hamideh and Khaki, Hossein and Erzin, Engin and Akan, Ozgur B},\n    booktitle = {2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},\n    pages = {3801--3805},\n    year = {2017},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Audio-facial laughter detection in naturalistic dyadic conversations.\n \n \n \n\n\n \n Turker, B. B.; Yemez, Y.; Sezgin, T M.; and Erzin, E.\n\n\n \n\n\n\n IEEE Transactions on Affective Computing, 8(4): 534–545. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{turker2017audio,\n    title = {Audio-facial laughter detection in naturalistic dyadic conversations},\n    author = {Turker, Bekir Berker and Yemez, Yucel and Sezgin, T Metin and Erzin, Engin},\n    journal = {IEEE Transactions on Affective Computing},\n    volume = {8},\n    number = {4},\n    pages = {534--545},\n    year = {2017},\n    publisher = {IEEE},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Empirical mode decomposition of throat microphone recordings for intake classification.\n \n \n \n\n\n \n Turan, M. T.; and Erzin, E.\n\n\n \n\n\n\n In Proceedings of the 2nd International Workshop on Multimedia for Personal Health and Health Care, pages 45–52, 2017. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@inproceedings{turan2017empirical,\n    title = {Empirical mode decomposition of throat microphone recordings for intake classification},\n    author = {Turan, MA Tu{\\u{g}}tekin and Erzin, Engin},\n    booktitle = {Proceedings of the 2nd International Workshop on Multimedia for Personal Health and Health Care},\n    pages = {45--52},\n    year = {2017},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Affect recognition from lip articulations.\n \n \n \n\n\n \n Sadiq, R.; and Erzin, E.\n\n\n \n\n\n\n In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 2432-2436, 2017. \n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{sadiq2017icassp,\n    author = {Sadiq, Rizwan and Erzin, Engin},\n    booktitle = {2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    title = {Affect recognition from lip articulations},\n    year = {2017},\n    pages = {2432-2436},\n    doi = {10.1109/ICASSP.2017.7952593}}
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\n \n\n \n \n \n \n \n \n Relational Symbol Grounding through Affordance Learning: An Overview of the ReGround Project.\n \n \n \n \n\n\n \n Antanas, L.; Can, O. A.; Davis, J.; De Raedt, L.; Loutfy, A.; Persson, A.; Saffiotti, A.; Ünal, E.; Yuret, D.; and Zuidberg dos Martires, P.\n\n\n \n\n\n\n In Grounding Language Understanding (GLU 2017) ISCA Satellite Workshop of Interspeech 2017, August 2017. Stockholm University\n \n\n\n\n
\n\n\n\n \n \n \"RelationalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{glu2017,\n    author = {Antanas, Laura and Can, Ozan Arkan and Davis, Jesse and De Raedt, Luc and Loutfy, Amy and Persson, Andreas and Saffiotti, Alessandro and \\"{U}nal, Emre and Yuret, Deniz and Zuidberg dos Martires, Pedro},\n    booktitle = {Grounding Language Understanding (GLU 2017) ISCA Satellite Workshop of Interspeech 2017},\n    year = {2017},\n    keywords = {ai.ku,NLP},\n    organization = {Stockholm University},\n    month = {August},\n    url = {http://www.isca-speech.org/archive/GLU_2017/pdfs/GLU2017_paper_3.pdf,http://www.isca-speech.org/archive/GLU_2017/abstracts/GLU2017_paper_3.html,http://www.isca-speech.org/archive/GLU_2017,/bib/antanas/glu2017/overview-reground-project.pdf,/bib/antanas/glu2017/jdavis-glu17-v2.pptx},\n    title = {Relational Symbol Grounding through Affordance Learning: An Overview of the {ReGround} Project},\n}\n\n
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\n \n\n \n \n \n \n \n \n RGB-D Object Recognition Using Deep Convolutional Neural Networks.\n \n \n \n \n\n\n \n Zia, S.; Yemez, Y.; and Yuret, D.\n\n\n \n\n\n\n In The IEEE International Conference on Computer Vision (ICCV), pages 896-903, October 2017. \n \n\n\n\n
\n\n\n\n \n \n \"RGB-DPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{zia2017rgbd,\n    author = {Zia, Saman and Yemez, Y\\"ucel and Yuret, Deniz},\n    year = {2017},\n    keywords = {ai.ku,NLP},\n    booktitle = {The IEEE International Conference on Computer Vision (ICCV)},\n    url = {/bib/zia/zia2017rgbd/rgb-d-object.pdf,http://openaccess.thecvf.com/content_ICCV_2017_workshops/w17/html/Zia_RGB-D_Object_Recognition_ICCV_2017_paper.html},\n    pages = {896-903},\n    month = {October},\n    title = {{RGB-D} Object Recognition Using Deep Convolutional Neural Networks},\n}\n\n
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\n \n\n \n \n \n \n \n \n A Dataset and Baseline System for Singing Voice Assessment.\n \n \n \n \n\n\n \n Bozkurt, B.; Baysal, O.; and Yuret, D.\n\n\n \n\n\n\n In The 13th International Symposium on Computer Music Multidisciplinary Research (CMMR), September 2017. \n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{bozkurt2017,\n    author = {Bozkurt, Bar\\i\\c{s} and Baysal, Ozan and Yuret, Deniz},\n    title = {A Dataset and Baseline System for Singing Voice Assessment},\n    booktitle = {The 13th International Symposium on Computer Music Multidisciplinary Research (CMMR)},\n    year = {2017},\n    keywords = {ai.ku,NLP},\n    month = {September},\n    annote = {25 September: http://cmmr2017.inesctec.pt/programme/scientific-programme/},\n    url = {http://cmmr2017.inesctec.pt/wp-content/uploads/2017/09/43_CMMR_2017_paper_31.pdf,/bib/bozkurt/bozkurt2017/cmmr2017_BozkurtBaysalYuret.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n Parsing with Context Embeddings.\n \n \n \n \n\n\n \n Kırnap, Ö.; Önder, B. F.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 80–87, Vancouver, Canada, August 2017. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"ParsingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{kirnap2017conll,\n    title = {Parsing with Context Embeddings},\n    year = {2017},\n    keywords = {ai.ku,NLP},\n    month = {August},\n    booktitle = {Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies},\n    url = {http://aclweb.org/anthology/K/K17/K17-3008.pdf,/bib/kirnap/kirnap2017conll/parsing-context-embeddings.pdf},\n    pages = {80--87},\n    address = {Vancouver, Canada},\n    publisher = {Association for Computational Linguistics},\n    author = {K{\\i}rnap, {\\"O}mer and {\\"O}nder, Berkay Furkan and Yuret, Deniz},\n}\n\n
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\n \n\n \n \n \n \n \n \n Learning to Follow Navigational Instructions.\n \n \n \n \n\n\n \n Can, O. A.; and Yuret, D.\n\n\n \n\n\n\n In International Symposium on Brain and Cognitive Science (ISBCS), Ankara, April 2017. Hacettepe University\n (invited talk)\n\n\n\n
\n\n\n\n \n \n \"LearningPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{can2017,\n    author = {Can, Ozan Arkan and Yuret, Deniz},\n    title = {Learning to Follow Navigational Instructions},\n    booktitle = {International Symposium on Brain and Cognitive Science (ISBCS)},\n    year = {2017},\n    keywords = {ai.ku,NLP},\n    address = {Ankara},\n    month = {April},\n    organization = {Hacettepe University},\n    note = {(invited talk)},\n    url = {/bib/can/can2017/navi-talk-deniz.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n Multidimensional Broadcast Operation on the GPU.\n \n \n \n \n\n\n \n Çoban, E. B.; Yuret, D.; and Unat, D.\n\n\n \n\n\n\n In 5. Ulusal Yüksek Başarımlı Hesaplama Konferansı, İstanbul, September 2017. \n \n\n\n\n
\n\n\n\n \n \n \"MultidimensionalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{coban2017,\n    author = {{\\c{C}}oban, Enis Berk and Yuret, Deniz and Unat, Didem},\n    booktitle = {5. Ulusal Y{\\"u}ksek Ba{\\c{s}}ar{\\i}ml{\\i} Hesaplama Konferans{\\i}},\n    year = {2017},\n    address = {{\\.I}stanbul},\n    month = {September},\n    keywords = {ai.ku,NLP},\n    url = {/bib/coban/coban2017/paper.pdf,https://drive.google.com/file/d/0B5_wxKFQbOTMbXVzTWhsbGFrZnM/view?usp=sharing},\n    title = {Multidimensional Broadcast Operation on the {GPU}},\n}\n\n
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\n  \n 2016\n \n \n (44)\n \n \n
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\n \n\n \n \n \n \n \n Multimodal analysis of speech and arm motion for prosody-driven synthesis of beat gestures.\n \n \n \n\n\n \n Bozkurt, E.; Yemez, Y.; and Erzin, E.\n\n\n \n\n\n\n Speech Commun., 85: 29-42. 2016.\n \n\n\n\n
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@article{Bozkurt2016MultimodalAO,\n    title = {Multimodal analysis of speech and arm motion for prosody-driven synthesis of beat gestures},\n    author = {E. Bozkurt and Y. Yemez and E. Erzin},\n    journal = {Speech Commun.},\n    year = {2016},\n    volume = {85},\n    pages = {29-42},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Deep Discrete Flow.\n \n \n \n\n\n \n Güney, F.; and Geiger, A.\n\n\n \n\n\n\n In ACCV, 2016. \n \n\n\n\n
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@inproceedings{Gney2016DeepDF,\n    title = {Deep Discrete Flow},\n    author = {Fatma G{\\"u}ney and Andreas Geiger},\n    booktitle = {ACCV},\n    year = {2016},\n    keywords = {CV},\n}\n\n
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\n \n\n \n \n \n \n \n Semantic Sketch-Based Video Retrieval with Autocompletion.\n \n \n \n\n\n \n Tanase, C.; Giangreco, I.; Rossetto, L.; Schuldt, H.; Seddati, O.; Dupont, S.; Altiok, O. C.; and Sezgin, T. M.\n\n\n \n\n\n\n Companion Publication of the 21st International Conference on Intelligent User Interfaces. 2016.\n \n\n\n\n
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@article{Tanase2016SemanticSV,\n    title = {Semantic Sketch-Based Video Retrieval with Autocompletion},\n    author = {C. Tanase and Ivan Giangreco and L. Rossetto and H. Schuldt and Omar Seddati and S. Dupont and Ozan Can Altiok and T. M. Sezgin},\n    journal = {Companion Publication of the 21st International Conference on Intelligent User Interfaces},\n    year = {2016},\n    keywords = {HCI},\n}\n\n
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\n \n\n \n \n \n \n \n Gaze-Based Biometric Authentication: Hand-Eye Coordination Patterns as a Biometric Trait.\n \n \n \n\n\n \n Çığ, Ç.; and Sezgin, T. M.\n\n\n \n\n\n\n In Expressive, 2016. \n \n\n\n\n
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@inproceedings{2016GazeBasedBA,\n    title = {Gaze-Based Biometric Authentication: Hand-Eye Coordination Patterns as a Biometric Trait},\n    author = {{\\c{C}}a{\\u{g}}la {\\c{C}}{\\i}{\\u{g}} and T. M. Sezgin},\n    booktitle = {Expressive},\n    year = {2016},\n    keywords = {HCI},\n}\n\n
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\n \n\n \n \n \n \n \n Compressed Training Adaptive MIMO equalization.\n \n \n \n\n\n \n Yilmaz, B. B.; and Erdogan, A. T.\n\n\n \n\n\n\n 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),1-6. 2016.\n \n\n\n\n
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@article{Yilmaz2016CompressedTA,\n    title = {Compressed Training Adaptive MIMO equalization},\n    author = {B. B. Yilmaz and Alper T. Erdogan},\n    journal = {2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)},\n    year = {2016},\n    pages = {1-6},\n    keywords = {ML},\n}\n\n
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\n \n\n \n \n \n \n \n Managed video services over multi-domain software defined networks.\n \n \n \n\n\n \n Bagci, K.; and Tekalp, A.\n\n\n \n\n\n\n 2016 24th European Signal Processing Conference (EUSIPCO),120-124. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{Bagci2016ManagedVS,\n    title = {Managed video services over multi-domain software defined networks},\n    author = {K. Bagci and A. Tekalp},\n    journal = {2016 24th European Signal Processing Conference (EUSIPCO)},\n    year = {2016},\n    pages = {120-124},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Dynamic end-to-end service-level negotiation over multi-domain software defined networks.\n \n \n \n\n\n \n Bagci, K.; Yilmaz, S.; Sahin, K. E.; and Tekalp, A.\n\n\n \n\n\n\n 2016 IEEE Sixth International Conference on Communications and Electronics (ICCE),33-39. 2016.\n \n\n\n\n
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@article{Bagci2016DynamicES,\n    title = {Dynamic end-to-end service-level negotiation over multi-domain software defined networks},\n    author = {K. Bagci and S. Yilmaz and Kemal E. Sahin and A. Tekalp},\n    journal = {2016 IEEE Sixth International Conference on Communications and Electronics (ICCE)},\n    year = {2016},\n    pages = {33-39},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Dynamic management of control plane performance in software-defined networks.\n \n \n \n\n\n \n Gorkemli, B.; Parlakisik, M.; Civanlar, S.; Ulas, A.; and Tekalp, A.\n\n\n \n\n\n\n 2016 IEEE NetSoft Conference and Workshops (NetSoft),68-72. 2016.\n \n\n\n\n
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@article{Gorkemli2016DynamicMO,\n    title = {Dynamic management of control plane performance in software-defined networks},\n    author = {B. Gorkemli and Murat Parlakisik and S. Civanlar and Aydin Ulas and A. Tekalp},\n    journal = {2016 IEEE NetSoft Conference and Workshops (NetSoft)},\n    year = {2016},\n    pages = {68-72},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n End-to-end service-level management framework over multi-domain software defined networks.\n \n \n \n\n\n \n Bagci, K.; Yilmaz, S.; Sahin, K. E.; and Tekalp, A.\n\n\n \n\n\n\n 2016 24th Signal Processing and Communication Application Conference (SIU),121-124. 2016.\n \n\n\n\n
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@article{Bagci2016EndtoendSM,\n    title = {End-to-end service-level management framework over multi-domain software defined networks},\n    author = {K. Bagci and S. Yilmaz and Kemal E. Sahin and A. Tekalp},\n    journal = {2016 24th Signal Processing and Communication Application Conference (SIU)},\n    year = {2016},\n    pages = {121-124},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Queue-allocation optimization for adaptive video streaming over software defined networks with multiple service-levels.\n \n \n \n\n\n \n Bagci, K.; Sahin, K. E.; and Tekalp, A.\n\n\n \n\n\n\n 2016 IEEE International Conference on Image Processing (ICIP),1519-1523. 2016.\n \n\n\n\n
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@article{Bagci2016QueueallocationOF,\n    title = {Queue-allocation optimization for adaptive video streaming over software defined networks with multiple service-levels},\n    author = {K. Bagci and Kemal E. Sahin and A. Tekalp},\n    journal = {2016 IEEE International Conference on Image Processing (ICIP)},\n    year = {2016},\n    pages = {1519-1523},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Use of Agreement/Disagreement Classification in Dyadic Interactions for Continuous Emotion Recognition.\n \n \n \n\n\n \n Khaki, H.; and Erzin, E.\n\n\n \n\n\n\n In INTERSPEECH, 2016. \n \n\n\n\n
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@inproceedings{Khaki2016UseOA,\n    title = {Use of Agreement/Disagreement Classification in Dyadic Interactions for Continuous Emotion Recognition},\n    author = {H. Khaki and E. Erzin},\n    booktitle = {INTERSPEECH},\n    year = {2016},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Source and Filter Estimation for Throat-Microphone Speech Enhancement.\n \n \n \n\n\n \n Turan, M.; and Erzin, E.\n\n\n \n\n\n\n IEEE/ACM Transactions on Audio, Speech, and Language Processing, 24: 265-275. 2016.\n \n\n\n\n
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@article{Turan2016SourceAF,\n    title = {Source and Filter Estimation for Throat-Microphone Speech Enhancement},\n    author = {M. Turan and E. Erzin},\n    journal = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},\n    year = {2016},\n    volume = {24},\n    pages = {265-275},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Agreement and disagreement classification of dyadic interactions using vocal and gestural cues.\n \n \n \n\n\n \n Khaki, H.; Bozkurt, E.; and Erzin, E.\n\n\n \n\n\n\n 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),2762-2766. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{Khaki2016AgreementAD,\n    title = {Agreement and disagreement classification of dyadic interactions using vocal and gestural cues},\n    author = {H. Khaki and E. Bozkurt and E. Erzin},\n    journal = {2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    year = {2016},\n    pages = {2762-2766},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n A subjective listening test of six different artificial bandwidth extension approaches in English, Chinese, German, and Korean.\n \n \n \n\n\n \n Abel, J.; Kaniewska, M.; Guillaume, C.; Tirry, W.; Pulakka, H.; Myllylä, V.; Sjoberg, J.; Alku, P.; Katsir, I.; Malah, D.; Cohen, I.; Turan, M.; Erzin, E.; Schlien, T.; Vary, P.; Nour-Eldin, A. H.; Kabal, P.; and Fingscheidt, T.\n\n\n \n\n\n\n 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),5915-5919. 2016.\n \n\n\n\n
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@article{Abel2016ASL,\n    title = {A subjective listening test of six different artificial bandwidth extension approaches in English, Chinese, German, and Korean},\n    author = {J. Abel and M. Kaniewska and C. Guillaume and Wouter Tirry and Hannu Pulakka and V. Myllyl{\\"a} and Jari Sjoberg and P. Alku and Itai Katsir and D. Malah and I. Cohen and M. Turan and E. Erzin and Thomas Schlien and P. Vary and Amr H. Nour-Eldin and P. Kabal and T. Fingscheidt},\n    journal = {2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    year = {2016},\n    pages = {5915-5919},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Natural Language Communication with Robots.\n \n \n \n\n\n \n Bisk, Y.; Yuret, D.; and Marcu, D.\n\n\n \n\n\n\n In HLT-NAACL, 2016. \n \n\n\n\n
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@inproceedings{Bisk2016NaturalLC,\n    title = {Natural Language Communication with Robots},\n    author = {Yonatan Bisk and Deniz Yuret and D. Marcu},\n    booktitle = {HLT-NAACL},\n    year = {2016},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Why Neural Translations are the Right Length.\n \n \n \n\n\n \n Shi, X.; Knight, K.; and Yuret, D.\n\n\n \n\n\n\n In EMNLP, 2016. \n \n\n\n\n
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@inproceedings{Shi2016WhyNT,\n    title = {Why Neural Translations are the Right Length},\n    author = {Xing Shi and Kevin Knight and Deniz Yuret},\n    booktitle = {EMNLP},\n    year = {2016},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n CharNER: Character-Level Named Entity Recognition.\n \n \n \n\n\n \n Kuru, O.; Can, O. A.; and Yuret, D.\n\n\n \n\n\n\n In COLING, 2016. \n \n\n\n\n
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@inproceedings{Kuru2016CharNERCN,\n    title = {CharNER: Character-Level Named Entity Recognition},\n    author = {Onur Kuru and Ozan Arkan Can and Deniz Yuret},\n    booktitle = {COLING},\n    year = {2016},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Transfer Learning for Low-Resource Neural Machine Translation.\n \n \n \n\n\n \n Zoph, B.; Yuret, D.; May, J.; and Knight, K.\n\n\n \n\n\n\n ArXiv, abs/1604.02201. 2016.\n \n\n\n\n
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\n 
@article{Zoph2016TransferLF,\n    title = {Transfer Learning for Low-Resource Neural Machine Translation},\n    author = {Barret Zoph and Deniz Yuret and Jonathan May and Kevin Knight},\n    journal = {ArXiv},\n    year = {2016},\n    volume = {abs/1604.02201},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Simultaneously learning actions and goals from demonstration.\n \n \n \n\n\n \n Akgün, B.; and Thomaz, A.\n\n\n \n\n\n\n Autonomous Robots, 40: 211-227. 2016.\n \n\n\n\n
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@article{Akgn2016SimultaneouslyLA,\n    title = {Simultaneously learning actions and goals from demonstration},\n    author = {Baris Akg{\\"u}n and A. Thomaz},\n    journal = {Autonomous Robots},\n    year = {2016},\n    volume = {40},\n    pages = {211-227},\n    keywords = {R},\n}\n\n
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\n \n\n \n \n \n \n \n Learning haptic affordances from demonstration and human-guided exploration.\n \n \n \n\n\n \n Chu, V.; Akgün, B.; and Thomaz, A.\n\n\n \n\n\n\n 2016 IEEE Haptics Symposium (HAPTICS),119-125. 2016.\n \n\n\n\n
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@article{Chu2016LearningHA,\n    title = {Learning haptic affordances from demonstration and human-guided exploration},\n    author = {Vivian Chu and Baris Akg{\\"u}n and A. Thomaz},\n    journal = {2016 IEEE Haptics Symposium (HAPTICS)},\n    year = {2016},\n    pages = {119-125},\n    keywords = {R},\n}\n\n
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\n \n\n \n \n \n \n \n Grounding action parameters from demonstration.\n \n \n \n\n\n \n Bullard, K.; Akgün, B.; Chernova, S.; and Thomaz, A.\n\n\n \n\n\n\n 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN),253-260. 2016.\n \n\n\n\n
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@article{Bullard2016GroundingAP,\n    title = {Grounding action parameters from demonstration},\n    author = {Kalesha Bullard and Baris Akg{\\"u}n and S. Chernova and A. Thomaz},\n    journal = {2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)},\n    year = {2016},\n    pages = {253-260},\n    keywords = {R},\n}\n\n
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\n \n\n \n \n \n \n \n Workload Management in Distributed Data Centers: Thermal and Spatial Awareness.\n \n \n \n\n\n \n Ali, A.; and Özkasap, Ö.\n\n\n \n\n\n\n 2016 IEEE International Conference on Smart Cloud (SmartCloud),158-163. 2016.\n \n\n\n\n
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@article{Ali2016WorkloadMI,\n    title = {Workload Management in Distributed Data Centers: Thermal and Spatial Awareness},\n    author = {A. Ali and {\\"O}znur {\\"O}zkasap},\n    journal = {2016 IEEE International Conference on Smart Cloud (SmartCloud)},\n    year = {2016},\n    pages = {158-163},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n SecVLC: Secure Visible Light Communication for Military Vehicular Networks.\n \n \n \n\n\n \n Ucar, S.; Ergen, S.; Özkasap, Ö.; Tsonev, D.; and Burchardt, H.\n\n\n \n\n\n\n Proceedings of the 14th ACM International Symposium on Mobility Management and Wireless Access. 2016.\n \n\n\n\n
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@article{Ucar2016SecVLCSV,\n    title = {SecVLC: Secure Visible Light Communication for Military Vehicular Networks},\n    author = {Seyhan Ucar and S. Ergen and {\\"O}znur {\\"O}zkasap and D. Tsonev and Harald Burchardt},\n    journal = {Proceedings of the 14th ACM International Symposium on Mobility Management and Wireless Access},\n    year = {2016},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Awake: Decentralized and Availability Aware Replication for P2P Cloud Storage.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n 2016 IEEE International Conference on Smart Cloud (SmartCloud),289-294. 2016.\n \n\n\n\n
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@article{HassanzadehNazarabadi2016AwakeDA,\n    title = {Awake: Decentralized and Availability Aware Replication for P2P Cloud Storage},\n    author = {Yahya Hassanzadeh-Nazarabadi and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    journal = {2016 IEEE International Conference on Smart Cloud (SmartCloud)},\n    year = {2016},\n    pages = {289-294},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Visible light communication in vehicular ad-hoc networks.\n \n \n \n\n\n \n Ucar, S.; Ergen, S.; and Özkasap, Ö.\n\n\n \n\n\n\n 2016 24th Signal Processing and Communication Application Conference (SIU),881-884. 2016.\n \n\n\n\n
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@article{Ucar2016VisibleLC,\n    title = {Visible light communication in vehicular ad-hoc networks},\n    author = {Seyhan Ucar and S. Ergen and {\\"O}znur {\\"O}zkasap},\n    journal = {2016 24th Signal Processing and Communication Application Conference (SIU)},\n    year = {2016},\n    pages = {881-884},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Price/cooling aware and delay sensitive scheduling in geographically distributed data centers.\n \n \n \n\n\n \n Ali, A.; and Özkasap, Ö.\n\n\n \n\n\n\n NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,1025-1030. 2016.\n \n\n\n\n
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@article{Ali2016PricecoolingAA,\n    title = {Price/cooling aware and delay sensitive scheduling in geographically distributed data centers},\n    author = {A. Ali and {\\"O}znur {\\"O}zkasap},\n    journal = {NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium},\n    year = {2016},\n    pages = {1025-1030},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n LARAS: Locality aware replication algorithm for the Skip Graph.\n \n \n \n\n\n \n Hassanzadeh-Nazarabadi, Y.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,324-332. 2016.\n \n\n\n\n
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@article{HassanzadehNazarabadi2016LARASLA,\n    title = {LARAS: Locality aware replication algorithm for the Skip Graph},\n    author = {Yahya Hassanzadeh-Nazarabadi and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    journal = {NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium},\n    year = {2016},\n    pages = {324-332},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Dimming support for visible light communication in intelligent transportation and traffic system.\n \n \n \n\n\n \n Ucar, S.; Turan, B.; Ergen, S.; Özkasap, Ö.; and Ergen, M.\n\n\n \n\n\n\n NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium,1193-1196. 2016.\n \n\n\n\n
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@article{Ucar2016DimmingSF,\n    title = {Dimming support for visible light communication in intelligent transportation and traffic system},\n    author = {Seyhan Ucar and B. Turan and S. Ergen and {\\"O}znur {\\"O}zkasap and M. Ergen},\n    journal = {NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium},\n    year = {2016},\n    pages = {1193-1196},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n TiDA: High-Level Programming Abstractions for Data Locality Management.\n \n \n \n\n\n \n Unat, D.; Nguyen, T.; Zhang, W.; Farooqi, M. N.; Bastem, B.; Michelogiannakis, G.; Almgren, A.; and Shalf, J.\n\n\n \n\n\n\n In ISC, 2016. \n \n\n\n\n
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@inproceedings{Unat2016TiDAHP,\n    title = {TiDA: High-Level Programming Abstractions for Data Locality Management},\n    author = {D. Unat and Tan Nguyen and W. Zhang and Muhammed Nufail Farooqi and Burak Bastem and George Michelogiannakis and A. Almgren and J. Shalf},\n    booktitle = {ISC},\n    year = {2016},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n Multihop-Cluster-Based IEEE 802.11p and LTE Hybrid Architecture for VANET Safety Message Dissemination.\n \n \n \n\n\n \n Ucar, S.; Ergen, S.; and Özkasap, Ö.\n\n\n \n\n\n\n IEEE Transactions on Vehicular Technology, 65: 2621-2636. 2016.\n \n\n\n\n
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@article{Ucar2016MultihopClusterBasedI8,\n    title = {Multihop-Cluster-Based IEEE 802.11p and LTE Hybrid Architecture for VANET Safety Message Dissemination},\n    author = {Seyhan Ucar and S. Ergen and {\\"O}znur {\\"O}zkasap},\n    journal = {IEEE Transactions on Vehicular Technology},\n    year = {2016},\n    volume = {65},\n    pages = {2621-2636},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n FlexDPDP: Flexlist-Based Optimized Dynamic Provable Data Possession.\n \n \n \n\n\n \n Esiner, E.; Kachkeev, A.; Braunfeld, S.; Küpçü, A.; and Özkasap, Ö.\n\n\n \n\n\n\n ACM Trans. Storage, 12: 23:1-23:44. 2016.\n \n\n\n\n
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@article{Esiner2016FlexDPDPFO,\n    title = {FlexDPDP: Flexlist-Based Optimized Dynamic Provable Data Possession},\n    author = {Ertem Esiner and Adilet Kachkeev and Samuel Braunfeld and Alptekin K{\\"u}p{\\c{c}}{\\"u} and {\\"O}znur {\\"O}zkasap},\n    journal = {ACM Trans. Storage},\n    year = {2016},\n    volume = {12},\n    pages = {23:1-23:44},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n A subjective listening test of six different artificial bandwidth extension approaches in English, Chinese, German, and Korean.\n \n \n \n\n\n \n Abel, J.; Kaniewska, M.; Guillaume, C.; Tirry, W.; Pulakka, H.; Myllylä, V.; Sjöberg, J.; Alku, P.; Katsir, I.; Malah, D.; and others\n\n\n \n\n\n\n In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 5915–5919, 2016. IEEE\n \n\n\n\n
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@inproceedings{abel2016subjective,\n    title = {A subjective listening test of six different artificial bandwidth extension approaches in English, Chinese, German, and Korean},\n    author = {Abel, Johannes and Kaniewska, Magdalena and Guillaume, Cyril and Tirry, Wouter and Pulakka, Hannu and Myllyl{\\"a}, Ville and Sj{\\"o}berg, Jari and Alku, Paavo and Katsir, Itai and Malah, David and others},\n    booktitle = {2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    pages = {5915--5919},\n    year = {2016},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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@inproceedings{khaki2016agreement,\n    title = {Agreement and disagreement classification of dyadic interactions using vocal and gestural cues},\n    author = {Khaki, Hossein and Bozkurt, Elif and Erzin, Engin},\n    booktitle = {2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},\n    pages = {2762--2766},\n    year = {2016},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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@inproceedings{kasarci2016real,\n    title = {Real-time speech driven gesture animation},\n    author = {Kasarc{\\i}, Kenan and Bozkurt, Elif and Yemez, Y{\\"u}cel and Erzin, Engin},\n    booktitle = {2016 24th Signal Processing and Communication Application Conference (SIU)},\n    pages = {1917--1920},\n    year = {2016},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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@inproceedings{kecceci2016analysis,\n    title = {Analysis of jestkod database using affective state annotations},\n    author = {Ke{\\c{c}}eci, Sinan and Erzin, Engin and Yemez, Y{\\"u}cel},\n    booktitle = {2016 24th Signal Processing and Communication Application Conference (SIU)},\n    pages = {1033--1036},\n    year = {2016},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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@inproceedings{turan2016food,\n    title = {Food intake classification using throat microphone},\n    author = {Turan, MA Tu{\\u{g}}tekin and Erzin, Engin},\n    booktitle = {2016 24th Signal Processing and Communication Application Conference (SIU)},\n    pages = {1873--1876},\n    year = {2016},\n    organization = {IEEE},\n    keywords = {MSP},\n}\n\n
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@inproceedings{khaki2016use,\n    title = {Use of Agreement/Disagreement Classification in Dyadic Interactions for Continuous Emotion Recognition.},\n    author = {Khaki, Hossein and Erzin, Engin},\n    booktitle = {INTERSPEECH},\n    pages = {605--609},\n    year = {2016},\n    keywords = {MSP},\n}\n\n
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\n \n\n \n \n \n \n \n Multimodal analysis of speech and arm motion for prosody-driven synthesis of beat gestures.\n \n \n \n\n\n \n Bozkurt, E.; Yemez, Y.; and Erzin, E.\n\n\n \n\n\n\n Speech Communication, 85: 29–42. 2016.\n \n\n\n\n
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@article{bozkurt2016multimodal,\n    title = {Multimodal analysis of speech and arm motion for prosody-driven synthesis of beat gestures},\n    author = {Bozkurt, Elif and Yemez, Y{\\"u}cel and Erzin, Engin},\n    journal = {Speech Communication},\n    volume = {85},\n    pages = {29--42},\n    year = {2016},\n    publisher = {North-Holland},\n    keywords = {MSP},\n}\n\n
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@inproceedings{yatbaz2013childes,\n    title = {Learning grammatical categories using paradigmatic representation: Substitute words for language acquisition},\n    keywords = {ai.ku,scode,NLP},\n    author = {Yatbaz, Mehmet Ali and Cirik, Volkan and K\\"untay, Aylin and Yuret, Deniz},\n    booktitle = {COLING},\n    year = {2016},\n    month = {December},\n    url = {https://aclweb.org/anthology/C/C16/C16-1068.pdf,/bib/yatbaz/yatbaz2013childes/383_Paper.pdf,/bib/yatbaz/yatbaz2013childes/383_Paper.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n Transfer Learning for Low-Resource Neural Machine Translation.\n \n \n \n \n\n\n \n Zoph, B.; Yuret, D.; May, J.; and Knight, K.\n\n\n \n\n\n\n In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 1568–1575, Austin, Texas, November 2016. Association for Computational Linguistics\n \n\n\n\n
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@inproceedings{zoph2016low,\n    title = {Transfer Learning for Low-Resource Neural Machine Translation},\n    year = {2016},\n    keywords = {ai.ku,NLP},\n    author = {Zoph, Barret and Yuret, Deniz and May, Jon and Knight, Kevin},\n    month = {November},\n    booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing},\n    url = {https://aclweb.org/anthology/D16-1163,http://arxiv.org/abs/1604.02201,https://www.overleaf.com/read/fwncntzcdmpj},\n    pages = {1568--1575},\n    address = {Austin, Texas},\n    publisher = {Association for Computational Linguistics},\n}\n\n
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\n\n\n\n \n \n \"WhyPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{shi2016length,\n    author = {Shi, Xing and Knight, Kevin and Yuret, Deniz},\n    title = {Why Neural Translations are the Right Length},\n    year = {2016},\n    keywords = {ai.ku,NLP},\n    month = {November},\n    url = {https://aclweb.org/anthology/D16-1248,https://www.overleaf.com/read/mkrvjhkgmdmr},\n    booktitle = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing},\n    pages = {2278--2282},\n    address = {Austin, Texas},\n    publisher = {Association for Computational Linguistics},\n}\n\n
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\n \n\n \n \n \n \n \n \n CharNER: Character-Level Named Entity Recognition.\n \n \n \n \n\n\n \n Kuru, O.; Can, O. A.; and Yuret, D.\n\n\n \n\n\n\n In COLING, December 2016. \n \n\n\n\n
\n\n\n\n \n \n \"CharNER:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{kuru2016charner,\n    author = {Kuru, Onur and Can, Ozan Arkan and Yuret, Deniz},\n    title = {CharNER: Character-Level Named Entity Recognition},\n    year = {2016},\n    keywords = {ai.ku,NLP},\n    booktitle = {COLING},\n    month = {December},\n    url = {https://aclweb.org/anthology/C/C16/C16-1087.pdf,/bib/kuru/kuru2016charner/376_Paper.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n Natural Language Communication with Robots.\n \n \n \n \n\n\n \n Bisk, Y.; Yuret, D.; and Marcu, D.\n\n\n \n\n\n\n In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 751–761, San Diego, California, June 2016. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"NaturalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{bisk-yuret-marcu:2016:N16-1,\n    author = {Bisk, Yonatan and Yuret, Deniz and Marcu, Daniel},\n    title = {Natural Language Communication with Robots},\n    booktitle = {Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},\n    month = {June},\n    year = {2016},\n    address = {San Diego, California},\n    publisher = {Association for Computational Linguistics},\n    pages = {751--761},\n    keywords = {ai.ku,NLP},\n    url = {http://www.aclweb.org/anthology/N16-1089},\n}\n\n
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\n \n\n \n \n \n \n \n \n Knet: beginning deep learning with 100 lines of Julia.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n In Machine Learning Systems Workshop at NIPS 2016, December 2016. \n \n\n\n\n
\n\n\n\n \n \n \"Knet:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yuret2016knet,\n    year = {2016},\n    keywords = {ai.ku,NLP},\n    author = {Yuret, Deniz},\n    month = {December},\n    booktitle = {Machine Learning Systems Workshop at NIPS 2016},\n    url = {/bib/yuret/yuret2016knet/knet-beginning-deep%20%283%29.pdf,https://goo.gl/KeOEoJ},\n    title = {Knet: beginning deep learning with 100 lines of {Julia}},\n}\n\n
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\n  \n 2015\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n Dual channel visible light communications for enhanced vehicular connectivity.\n \n \n \n\n\n \n Turan, B.; Ucar, S.; Ergen, S.; and Özkasap, Ö.\n\n\n \n\n\n\n 2015 IEEE Vehicular Networking Conference (VNC),84-87. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@article{Turan2015DualCV,\n    title = {Dual channel visible light communications for enhanced vehicular connectivity},\n    author = {B. Turan and Seyhan Ucar and S. Ergen and {\\"O}znur {\\"O}zkasap},\n    journal = {2015 IEEE Vehicular Networking Conference (VNC)},\n    year = {2015},\n    pages = {84-87},\n    keywords = {SAI},\n}\n\n
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\n \n\n \n \n \n \n \n \n Optimizing Instance Selection for Statistical Machine Translation with Feature Decay Algorithms.\n \n \n \n \n\n\n \n Biçici, E.; and Yuret, D.\n\n\n \n\n\n\n IEEE Transactions on Audio, Speech and Language Processing, 23(2): 339–350. February 2015.\n \n\n\n\n
\n\n\n\n \n \n \"OptimizingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{bicici2014fda,\n    title = {Optimizing Instance Selection for Statistical Machine Translation with Feature Decay Algorithms},\n    journal = {IEEE Transactions on Audio, Speech and Language Processing},\n    keywords = {ai.ku,NLP},\n    author = {Bi{\\c{c}}ici, Ergun and Yuret, Deniz},\n    year = {2015},\n    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6987314,/bib/bicici/bicici2014fda/FDA_TASLP1.pdf},\n    volume = {23},\n    number = {2},\n    pages = {339--350},\n    month = {February},\n    publisher = {IEEE},\n    doi = {10.1109/TASLP.2014.2381882},\n}\n\n
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\n \n\n \n \n \n \n \n Functionally important residues from mode coupling during short-time protein dynamics.\n \n \n \n\n\n \n Kabakcioglu, A.; Varol, O.; Yuret, D.; and Erman, B.\n\n\n \n\n\n\n In APS Meeting Abstracts, volume 1, pages 48009, 2015. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{kabakcioglu2015functionally,\n    title = {Functionally important residues from mode coupling during short-time protein dynamics},\n    author = {Kabakcioglu, Alkan and Varol, Onur and Yuret, Deniz and Erman, Burak},\n    booktitle = {APS Meeting Abstracts},\n    volume = {1},\n    pages = {48009},\n    year = {2015},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Functionally Important Residues from Mode Coupling during Short-Time Protein Dynamics.\n \n \n \n\n\n \n Varol, O.; Yuret, D.; Erman, B.; and Kabakcioglu, A.\n\n\n \n\n\n\n Biophysical Journal, 108(2): 377a. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{varol2015functionally,\n    title = {Functionally Important Residues from Mode Coupling during Short-Time Protein Dynamics},\n    author = {Varol, Onur and Yuret, Deniz and Erman, Burak and Kabakcioglu, Alkan},\n    journal = {Biophysical Journal},\n    volume = {108},\n    number = {2},\n    pages = {377a},\n    year = {2015},\n    publisher = {Elsevier},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n  \n 2014\n \n \n (8)\n \n \n
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\n \n\n \n \n \n \n \n Paradigmatic representations outperform syntagmatic representations in distributional learning of grammatical categories.\n \n \n \n\n\n \n Yatbaz, M. A.; Cirik, V.; Küntay, A.; and Yuret, D.\n\n\n \n\n\n\n In BUCLD, November 2014. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yatbaz2014bucld,\n    title = {Paradigmatic representations outperform syntagmatic representations in distributional learning of grammatical categories},\n    booktitle = {BUCLD},\n    year = {2014},\n    keywords = {ai.ku,scode,NLP},\n    month = {November},\n    author = {Yatbaz, Mehmet Ali and Cirik, Volkan and K\\"untay, Aylin and Yuret, Deniz},\n}\n\n
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\n \n\n \n \n \n \n \n \n Probabilistic Modeling of Joint-context in Distributional Similarity.\n \n \n \n \n\n\n \n Melamud, O.; Dagan, I.; Goldberger, J.; Szpektor, I.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the Eighteenth Conference on Computational Natural Language Learning, pages 181–190, Ann Arbor, Michigan, June 2014. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"ProbabilisticPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{melamud-EtAl:2014:W14-16,\n    author = {Melamud, Oren and Dagan, Ido and Goldberger, Jacob and Szpektor, Idan and Yuret, Deniz},\n    title = {Probabilistic Modeling of Joint-context in Distributional Similarity},\n    booktitle = {Proceedings of the Eighteenth Conference on Computational Natural Language Learning},\n    month = {June},\n    year = {2014},\n    address = {Ann Arbor, Michigan},\n    publisher = {Association for Computational Linguistics},\n    pages = {181--190},\n    keywords = {ai.ku,scode,NLP},\n    url = {http://www.aclweb.org/anthology/W14-1619,/bib/melamud/melamud-EtAl%3A2014%3AW14-16/W14-1619.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n Substitute Based SCODE Word Embeddings in Supervised NLP Tasks.\n \n \n \n \n\n\n \n Cirik, V.; and Yuret, D.\n\n\n \n\n\n\n Jul 2014.\n ArXiv e-prints\n\n\n\n
\n\n\n\n \n \n \"SubstitutePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@unpublished{2014arXiv1407.6853C,\n    title = {{Substitute Based SCODE Word Embeddings in Supervised NLP Tasks}},\n    keywords = {ai.ku,scode,NLP},\n    year = {2014},\n    url = {http://arxiv.org/abs/1407.6853v1},\n    month = {Jul},\n    note = {ArXiv e-prints},\n    author = {Cirik, Volkan and Yuret, Deniz},\n}\n\n
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\n \n\n \n \n \n \n \n \n Parsing Without Words or POS Tags: Dense Word Vectors Capture Sufficient Syntactic Information.\n \n \n \n \n\n\n \n Cirik, V.; Sensoy, H.; and Yuret, D.\n\n\n \n\n\n\n In The LTI Student Research Symposium), August 2014. \n \n\n\n\n
\n\n\n\n \n \n \"ParsingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{cirik2014b,\n    author = {Cirik, Volkan and Sensoy, Husnu and Yuret, Deniz},\n    title = {{Parsing Without Words or POS Tags: Dense Word Vectors Capture Sufficient Syntactic Information}},\n    booktitle = {The LTI Student Research Symposium)},\n    month = {August},\n    year = {2014},\n    keywords = {ai.ku,scode,NLP},\n    url = {https://drive.google.com/file/d/0B6C4-zOYlkxsQ1haakV0MVo4NjVnUXFLRVQ3cEV2U2lyaGo4/edit?usp=sharing,http://goo.gl/HAVNGW},\n}\n\n
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\n \n\n \n \n \n \n \n \n Context-Aware Word Vectors using Substitute Word Distributions.\n \n \n \n \n\n\n \n Cirik, V.; and Yuret, D.\n\n\n \n\n\n\n In The LTI Student Research Symposium), August 2014. \n \n\n\n\n
\n\n\n\n \n \n \"Context-AwarePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@inproceedings{cirik2014c,\n    title = {{Context-Aware Word Vectors using Substitute Word Distributions}},\n    booktitle = {The LTI Student Research Symposium)},\n    month = {August},\n    year = {2014},\n    author = {Cirik, Volkan and Yuret, Deniz},\n    keywords = {ai.ku,scode,NLP},\n    url = {https://drive.google.com/file/d/0B6C4-zOYlkxsWEJ4VVRtc3lURGtyd0Y2bThjb1V6TkZpQ3ZZ/edit?usp=sharing,http://goo.gl/rT8xqk},\n}\n\n
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\n \n\n \n \n \n \n \n \n Unsupervised Instance-Based Part of Speech Induction Using Probable Substitutes.\n \n \n \n \n\n\n \n Yuret, D.; Yatbaz, M. A.; and Sert, E.\n\n\n \n\n\n\n In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, pages 2303–2313, Dublin, Ireland, August 2014. Dublin City University and Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"UnsupervisedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@inproceedings{yuret-yatbaz-sert:2014:Coling,\n    author = {Yuret, Deniz and Yatbaz, Mehmet Ali and Sert, Enis},\n    title = {Unsupervised Instance-Based Part of Speech Induction Using Probable Substitutes},\n    booktitle = {Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers},\n    month = {August},\n    year = {2014},\n    address = {Dublin, Ireland},\n    publisher = {Dublin City University and Association for Computational Linguistics},\n    pages = {2303--2313},\n    url = {http://www.aclweb.org/anthology/C14-1217},\n    keywords = {ai.ku,scode,NLP},\n}\n\n
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\n \n\n \n \n \n \n \n \n Mode coupling points to functionally important residues in myosin II.\n \n \n \n \n\n\n \n Varol, O.; Yuret, D.; Erman, B.; and Kabakçıoğlu, A.\n\n\n \n\n\n\n Proteins: Structure, Function, and Bioinformatics, 82(9): 1777–1786. September 2014.\n \n\n\n\n
\n\n\n\n \n \n \"ModePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{PROT:PROT24531,\n    author = {Varol, Onur and Yuret, Deniz and Erman, Burak and Kabak{\\c{c}}{\\i}o{\\u{g}}lu, Alkan},\n    journal = {Proteins: Structure, Function, and Bioinformatics},\n    volume = {82},\n    number = {9},\n    issn = {1097-0134},\n    url = {http://dx.doi.org/10.1002/prot.24531},\n    doi = {test},\n    pages = {1777--1786},\n    year = {2014},\n    month = {September},\n    keywords = {ai.ku,NLP},\n    title = {Mode coupling points to functionally important residues in myosin {II}},\n}\n\n
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\n \n\n \n \n \n \n \n \n Special Issue: Computational Models of Narrative.\n \n \n \n \n\n\n \n Finlayson, M. A.; Bex, F.; Gervás, P.; and Yuret, D.\n\n\n \n\n\n\n Literary and Linguistic Computing, 29(4): 465-466. 2014.\n \n\n\n\n
\n\n\n\n \n \n \"SpecialPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@article{Finlayson01122014,\n    author = {Finlayson, Mark A. and Bex, Floris and Gervás, Pablo and Yuret, Deniz},\n    title = {Special Issue: Computational Models of Narrative},\n    volume = {29},\n    number = {4},\n    pages = {465-466},\n    year = {2014},\n    doi = {10.1093/llc/fqu053},\n    url = {http://llc.oxfordjournals.org/content/29/4/465.short,http://llc.oxfordjournals.org/content/29/4/465.full.pdf+html},\n    journal = {Literary and Linguistic Computing},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n  \n 2013\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n \n AI-KU: Using Substitute Vectors and Co-Occurrence Modeling For Word Sense Induction and Disambiguation.\n \n \n \n \n\n\n \n Başkaya, O.; Sert, E.; Cirik, V.; and Yuret, D.\n\n\n \n\n\n\n In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), pages 300–306, Atlanta, Georgia, USA, June 2013. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"AI-KU:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
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@inproceedings{baskaya-EtAl:2013:SemEval-2013,\n    booktitle = {Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)},\n    month = {June},\n    year = {2013},\n    address = {Atlanta, Georgia, USA},\n    publisher = {Association for Computational Linguistics},\n    pages = {300--306},\n    url = {http://www.aclweb.org/anthology/S13-2050},\n    keywords = {ai.ku,scode,NLP},\n    author = {Ba{\\c{s}}kaya, Osman and Sert, Enis and Cirik, Volkan and Yuret, Deniz},\n    title = {{AI-KU}: Using Substitute Vectors and Co-Occurrence Modeling For Word Sense Induction and Disambiguation},\n}\n\n
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\n \n\n \n \n \n \n \n \n A Language Visualization System.\n \n \n \n \n\n\n \n Unal, E.; and Yuret, D.\n\n\n \n\n\n\n In The Second Workshop on Games and NLP (GAMNLP-13), Istanbul, November 2013. \n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@inproceedings{unal2013visualisation,\n    author = {Unal, Emre and Yuret, Deniz},\n    title = {A Language Visualization System},\n    booktitle = {The Second Workshop on Games and NLP (GAMNLP-13)},\n    year = {2013},\n    address = {Istanbul},\n    month = {November},\n    keywords = {ai.ku,NLP},\n    url = {/bib/unal/unal2013visualisation/emre-gamenlp13-rev2.pdf},\n}\n\n
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\n \n\n \n \n \n \n \n \n Ontology for use with a system, method, and computer readable medium for retrieving information and response to a query.\n \n \n \n \n\n\n \n Cooper, E. R.; Bierner, G.; Graham, L. K.; Yuret, D.; Williams, J. C.; and Beghelli, F.\n\n\n \n\n\n\n US Patent Number 8612208, 9747390, Dec 2013.\n \n\n\n\n
\n\n\n\n \n \n \"OntologyPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@misc{yuret2013pat,\n    keywords = {ai.ku,NLP},\n    title = {Ontology for use with a system, method, and computer readable medium for retrieving information and response to a query},\n    howpublished = {US Patent Number 8612208, 9747390},\n    month = {Dec},\n    year = {2013},\n    url = {http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=2&f=G&l=50&co1=AND&d=PTXT&s1=yuret.INNM.&OS=IN/yuret&RS=IN/yuret,http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PTXT&s1=yuret.INNM.&OS=IN/yuret&RS=IN/yuret},\n    author = {Cooper, Edwin Riley and Bierner, Gann and Graham, Laurel Kathleen and Yuret, Deniz and Williams, James Charles and Beghelli, Filippo},\n}\n\n
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\n  \n 2012\n \n \n (3)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n \n Learning Syntactic Categories Using Paradigmatic Representations of Word Context.\n \n \n \n \n\n\n \n Yatbaz, M. A.; Sert, E.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the 2012 Conference on Empirical Methods in Natural Language Processing (EMNLP-CONLL 2012), Jeju, Korea, July 2012. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"LearningPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yuret2012upos,\n    author = {Yatbaz, Mehmet Ali and Sert, Enis and Yuret, Deniz},\n    title = {Learning Syntactic Categories Using Paradigmatic Representations of Word Context},\n    booktitle = {Proceedings of the 2012 Conference on Empirical Methods in Natural Language Processing (EMNLP-CONLL 2012)},\n    year = {2012},\n    url = {http://denizyuret.blogspot.com/2012/05/learning-syntactic-categories-using.html},\n    address = {Jeju, Korea},\n    month = {July},\n    publisher = {Association for Computational Linguistics},\n    keywords = {ai.ku,fulbright,scode,upos,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n FASTSUBS: An Efficient and Exact Procedure for Finding the Most Likely Lexical Substitutes Based on an N-gram Language Model.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n Signal Processing Letters, IEEE, 19(11): 725–728. November 2012.\n \n\n\n\n
\n\n\n\n \n \n \"FASTSUBS:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{yuret2012fastsubs,\n    journal = {Signal Processing Letters, IEEE},\n    title = {FASTSUBS: An Efficient and Exact Procedure for Finding the Most Likely Lexical Substitutes Based on an N-gram Language Model},\n    year = {2012},\n    doi = {10.1109/LSP.2012.2215587},\n    issn = {1070-9908},\n    keywords = {ai.ku,scode,NLP},\n    author = {Yuret, Deniz},\n    volume = {19},\n    number = {11},\n    pages = {725--728},\n    month = {November},\n    publisher = {IEEE Signal Processing Society},\n    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6287552,http://www.denizyuret.com/2012/05/fastsubs-efficient-admissible-algorithm.html},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Parser Evaluation Using Textual Entailments.\n \n \n \n \n\n\n \n Yuret, D.; Rimell, L.; and Han, A.\n\n\n \n\n\n\n Language Resources and Evaluation, 47(3): 639–659. September 2012.\n \n\n\n\n
\n\n\n\n \n \n \"ParserPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{pete2012,\n    author = {Yuret, Deniz and Rimell, Laura and Han, Aydin},\n    title = {Parser Evaluation Using Textual Entailments},\n    year = {2012},\n    journal = {Language Resources and Evaluation},\n    publisher = {Springer},\n    keywords = {ai.ku,NLP},\n    doi = {10.1007/s10579-012-9200-5},\n    url = {/bib/yuret/pete2012/pete-long.pdf},\n    volume = {47},\n    number = {3},\n    pages = {639--659},\n    month = {September},\n}\n\n
\n
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\n\n
\n
\n  \n 2011\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Instance Selection for Machine Translation using Feature Decay Algorithms.\n \n \n \n \n\n\n \n Biçici, E.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the Sixth Workshop on Statistical Machine Translation, pages 272–283, Edinburgh, Scotland, July 2011. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"InstancePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{bicici-yuret:2011:WMT1,\n    title = {Instance Selection for Machine Translation using Feature Decay Algorithms},\n    booktitle = {Proceedings of the Sixth Workshop on Statistical Machine Translation},\n    month = {July},\n    year = {2011},\n    address = {Edinburgh, Scotland},\n    publisher = {Association for Computational Linguistics},\n    pages = {272--283},\n    url = {http://www.aclweb.org/anthology/W11-2131.pdf,/bib/bicici/bicici-yuret/ISforMTFDA_WMT11Presentation.pdf},\n    keywords = {ai.ku,NLP},\n    author = {Bi{\\c{c}}ici, Ergun and Yuret, Deniz},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n RegMT System for Machine Translation, System Combination, and Evaluation.\n \n \n \n \n\n\n \n Biçici, E.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the Sixth Workshop on Statistical Machine Translation, pages 323–329, Edinburgh, Scotland, July 2011. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"RegMTPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{bicici-yuret:2011:WMT2,\n    title = {RegMT System for Machine Translation, System Combination, and Evaluation},\n    booktitle = {Proceedings of the Sixth Workshop on Statistical Machine Translation},\n    month = {July},\n    year = {2011},\n    address = {Edinburgh, Scotland},\n    publisher = {Association for Computational Linguistics},\n    pages = {323--329},\n    url = {http://www.aclweb.org/anthology/W11-2137.pdf},\n    keywords = {ai.ku,NLP},\n    author = {Bi{\\c{c}}ici, Ergun and Yuret, Deniz},\n}\n\n
\n
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\n\n
\n
\n  \n 2010\n \n \n (4)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n The Noisy Channel Model for Unsupervised Word Sense Disambiguation.\n \n \n \n \n\n\n \n Yuret, D.; and Yatbaz, M. A.\n\n\n \n\n\n\n Computational Linguistics, 36(1): 111–127. March 2010.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{Yuret2010coli,\n    title = {The Noisy Channel Model for Unsupervised Word Sense Disambiguation},\n    author = {Yuret, Deniz and Yatbaz, Mehmet Ali},\n    journal = {Computational Linguistics},\n    year = {2010},\n    volume = {36},\n    number = {1},\n    month = {March},\n    publisher = {MIT Press},\n    pages = {111--127},\n    keywords = {ai.ku,fulbright,NLP},\n    url = {http://aclweb.org/anthology/J/J10/J10-1004.pdf},\n}\n\n
\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Anharmonicity, mode-coupling and entropy in a fluctuating native protein.\n \n \n \n \n\n\n \n Kabakçıoğlu, A.; Yuret, D.; Gür, M.; and Erman, B.\n\n\n \n\n\n\n Physical Biology, 7: 046005. October 2010.\n \n\n\n\n
\n\n\n\n \n \n \"Anharmonicity,Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{kabakcioglu2010anharmonicity,\n    title = {{Anharmonicity, mode-coupling and entropy in a fluctuating native protein}},\n    journal = {Physical Biology},\n    volume = {7},\n    pages = {046005},\n    year = {2010},\n    publisher = {IOP Publishing},\n    url = {http://denizyuret.blogspot.com/2010/10/anharmonicity-mode-coupling-and-entropy.html},\n    keywords = {ai.ku,NLP},\n    month = {October},\n    author = {Kabak{\\c{c}}{\\i}o{\\u{g}}lu, Alkan and Yuret, Deniz and G{\\"u}r, Mert and Erman, Burak},\n}\n\n
\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Unsupervised part of speech tagging using unambiguous substitutes from a statistical language model.\n \n \n \n \n\n\n \n Yatbaz, M. A.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the 23rd International Conference on Computational Linguistics: Posters, pages 1391–1398, August 2010. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"UnsupervisedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yatbaz2010unsupervised,\n    title = {{Unsupervised part of speech tagging using unambiguous substitutes from a statistical language model}},\n    booktitle = {Proceedings of the 23rd International Conference on Computational Linguistics: Posters},\n    pages = {1391--1398},\n    year = {2010},\n    organization = {Association for Computational Linguistics},\n    month = {August},\n    keywords = {ai.ku,fulbright,scode,NLP},\n    url = {http://denizyuret.blogspot.com/2010/08/unsupervised-part-of-speech-tagging.html},\n    author = {Yatbaz, Mehmet Ali and Yuret, Deniz},\n}\n\n
\n
\n\n\n\n
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\n \n\n \n \n \n \n \n \n Preprocessing with Linear Transformations that Maximize the Nearest Neighbor Classification Accuracy.\n \n \n \n \n\n\n \n Yatbaz, M. A.; and Yuret, D.\n\n\n \n\n\n\n In 1st CSE Student Workshop (CSW'10), February 2010. \n \n\n\n\n
\n\n\n\n \n \n \"PreprocessingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yatbaz2010csw,\n    title = {Preprocessing with Linear Transformations that Maximize the Nearest Neighbor Classification Accuracy},\n    booktitle = {1st CSE Student Workshop (CSW'10)},\n    year = {2010},\n    month = {February},\n    url = {http://denizyuret.blogspot.com/2010/02/preprocessing-with-linear.html},\n    keywords = {ai.ku,NLP},\n    author = {Yatbaz, Mehmet Ali and Yuret, Deniz},\n}\n\n
\n
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\n
\n  \n 2009\n \n \n (4)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Morphological cues vs. number of nominals in learning verb types in Turkish: Syntactic bootstrapping mechanism revisited.\n \n \n \n \n\n\n \n Ural, A. E.; Yuret, D.; Ketrez, N.; Kocbas, D.; and Kuntay, A.\n\n\n \n\n\n\n Language and Cognitive Processes, 24(10): 1393–1405. December 2009.\n \n\n\n\n
\n\n\n\n \n \n \"MorphologicalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{Ural2009,\n    author = {Ural, A. Engin and Yuret, Deniz and Ketrez, Nihan and Kocbas, Dilara and Kuntay, Aylin},\n    title = {Morphological cues vs. number of nominals in learning verb types in Turkish: Syntactic bootstrapping mechanism revisited},\n    year = {2009},\n    journal = {Language and Cognitive Processes},\n    url = {/research/2008/trverb/paper/submitted/COGNIT-S-08-00510[1].pdf,http://springerlink.com/content/cr044066132q4u15},\n    volume = {24},\n    number = {10},\n    pages = {1393--1405},\n    month = {December},\n    publisher = {Psychology Press},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Classification of Semantic Relations between Nominals.\n \n \n \n \n\n\n \n Girju, R.; Nakov, P.; Nastase, V.; Szpakowicz, S.; Turney, P.; and Yuret, D.\n\n\n \n\n\n\n Language Resources and Evaluation, 43(2): 105–121. June 2009.\n \n\n\n\n
\n\n\n\n \n \n \"ClassificationPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{Girju2009,\n    author = {Girju, Roxana and Nakov, Preslav and Nastase, Vivi and Szpakowicz, Stan and Turney, Peter and Yuret, Deniz},\n    title = {Classification of Semantic Relations between Nominals},\n    year = {2009},\n    journal = {Language Resources and Evaluation},\n    volume = {43},\n    number = {2},\n    url = {/research/2008/lre08srn/published/fulltext.pdf,http://springerlink.com/content/cr044066132q4u15},\n    pages = {105--121},\n    month = {June},\n    publisher = {Springer},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Modeling Morphologically Rich Languages Using Split Words and Unstructured Dependencies.\n \n \n \n \n\n\n \n Yuret, D.; and Biçici, E.\n\n\n \n\n\n\n In ACL-IJCNLP, Singapore, August 2009. \n \n\n\n\n
\n\n\n\n \n \n \"ModelingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret2009asl,\n    title = {Modeling Morphologically Rich Languages Using Split Words and Unstructured Dependencies},\n    year = {2009},\n    booktitle = {ACL-IJCNLP},\n    month = {August},\n    address = {Singapore},\n    url = {http://aclweb.org/anthology/P/P09/P09-2087.pdf,/research/2009/trmodel/final-submit/ModelingMorphologicallyRichLanguages.pdf},\n    keywords = {ai.ku,SLM,comp542,NLP},\n    author = {Yuret, Deniz and Bi{\\c{c}}ici, Ergun},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Unsupervised morphological disambiguation using statistical language models.\n \n \n \n \n\n\n \n Yatbaz, M. A.; and Yuret, D.\n\n\n \n\n\n\n In NIPS 2009 Workshop on Grammar Induction, Representation of Language and Language Learning, Vancouver, Canada, December 2009. \n \n\n\n\n
\n\n\n\n \n \n \"UnsupervisedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yuret2009nips,\n    author = {Yatbaz, Mehmet Ali and Yuret, Deniz},\n    title = {Unsupervised morphological disambiguation using statistical language models},\n    booktitle = {NIPS 2009 Workshop on Grammar Induction, Representation of Language and Language Learning},\n    year = {2009},\n    month = {December},\n    address = {Vancouver, Canada},\n    keywords = {ai.ku,fulbright,scode,NLP},\n    url = {http://denizyuret.blogspot.com/2009/12/unsupervised-morphological.html},\n}\n\n
\n
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\n\n
\n
\n  \n 2008\n \n \n (4)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Discriminative vs. Generative Approaches in Semantic Role Labeling.\n \n \n \n \n\n\n \n Yuret, D.; Yatbaz, M. A.; and Ural, A. E.\n\n\n \n\n\n\n In Conference on Computational Natural Language Learning (CoNLL), Manchaster, UK, Aug 2008. \n \n\n\n\n
\n\n\n\n \n \n \"DiscriminativePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret2008conll,\n    author = {Yuret, Deniz and Yatbaz, Mehmet Ali and Ural, Ahmet Engin},\n    title = {Discriminative vs. Generative Approaches in Semantic Role Labeling},\n    booktitle = {Conference on Computational Natural Language Learning (CoNLL)},\n    year = {2008},\n    keywords = {SRL,ai.ku,NLP},\n    address = {Manchaster, UK},\n    month = {Aug},\n    url = {/pub/conll08st/paper/7_Paper.pdf},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Morphological Cues vs. Number of Nominals in Learning Verb Types from Child-Directed Speech.\n \n \n \n \n\n\n \n Yuret, D.; Ural, A. E.; Ketrez, F. N.; Kocbas, D.; and Kuntay, A. C.\n\n\n \n\n\n\n In Boston University Conference on Language Development (BUCLD33), October 2008. \n \n\n\n\n
\n\n\n\n \n \n \"MorphologicalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yuret2008bucld,\n    author = {Yuret, Deniz and Ural, A. Engin and Ketrez, F. Nihan and Kocbas, Dilara and Kuntay, Aylin C.},\n    url = {/research/2008/bucld33/BUCLD33Abstract3.doc,/research/2008/bucld33/BUCLD2008AK.ppt},\n    title = {Morphological Cues vs. Number of Nominals in Learning Verb Types from Child-Directed Speech},\n    month = {October},\n    year = {2008},\n    keywords = {ai.ku,NLP},\n    booktitle = {Boston University Conference on Language Development (BUCLD33)},\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Parser Training and Evaluation using Textual Entailments (A Task Proposal).\n \n \n \n \n\n\n \n Yuret, D.; and Eker, O.\n\n\n \n\n\n\n 2008.\n \n\n\n\n
\n\n\n\n \n \n \"ParserPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@misc{Yuret2008pete,\n    url = {/research/2008/pete/pete.pdf},\n    author = {Yuret, Deniz and Eker, Onder},\n    title = {Parser Training and Evaluation using Textual Entailments (A Task Proposal)},\n    year = {2008},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Smoothing a Tera-word Language Model.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n In Proceedings of ACL-08: HLT, Short Papers, pages 141–144, Columbus, Ohio, June 2008. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"SmoothingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yuret:2008:ACLShort,\n    author = {Yuret, Deniz},\n    title = {Smoothing a Tera-word Language Model},\n    booktitle = {Proceedings of ACL-08: HLT, Short Papers},\n    month = {June},\n    year = {2008},\n    address = {Columbus, Ohio},\n    publisher = {Association for Computational Linguistics},\n    pages = {141--144},\n    keywords = {SLM,cl09bib,ai.ku,comp542,NLP},\n    url = {http://www.aclweb.org/anthology/P/P08/P08-2036.pdf},\n}\n\n
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\n  \n 2007\n \n \n (6)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Locally Scaled Density Based Clustering.\n \n \n \n \n\n\n \n Biçici, E.; and Yuret, D.\n\n\n \n\n\n\n In Beliczynski, B.; and others, editor(s), ICANNGA 2007, Part I, LNCS 4431, pages 739–748, Berlin Heidelberg, April 2007. Springer-Verlag\n \n\n\n\n
\n\n\n\n \n \n \"LocallyPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret2007a,\n    title = {Locally Scaled Density Based Clustering},\n    year = {2007},\n    author = {Bi{\\c{c}}ici, Ergun and Yuret, Deniz},\n    month = {April},\n    url = {/pub/icannga07/LSDBC-icannga07.pdf},\n    booktitle = {ICANNGA 2007, Part I, LNCS 4431},\n    editor = {Beliczynski, B. and others},\n    pages = {739--748},\n    address = {Berlin Heidelberg},\n    publisher = {Springer-Verlag},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n SemEval-2007 Task 04: Classification of Semantic Relations between Nominals.\n \n \n \n \n\n\n \n Girju, R.; Nakov, P.; Nastase, V.; Szpakowicz, S.; Turney, P.; and Yuret, D.\n\n\n \n\n\n\n In SemEval-2007: 4th International Workshop on Semantic Evaluations, June 2007. \n \n\n\n\n
\n\n\n\n \n \n \"SemEval-2007Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Girju2007,\n    author = {Girju, Roxana and Nakov, Preslav and Nastase, Vivi and Szpakowicz, Stan and Turney, Peter and Yuret, Deniz},\n    year = {2007},\n    title = {SemEval-2007 Task 04: Classification of Semantic Relations between Nominals},\n    month = {June},\n    booktitle = {SemEval-2007: 4th International Workshop on Semantic Evaluations},\n    url = {/pub/semeval07-task04/task4final.pdf},\n    keywords = {semeval07.bib,ai.ku,NLP},\n}\n\n
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\n \n\n \n \n \n \n \n \n The CoNLL 2007 Shared Task on Dependency Parsing.\n \n \n \n \n\n\n \n Nivre, J.; Hall, J.; Kübler, S.; McDonald, R.; Nilsson, J.; Riedel, S.; and Yuret, D.\n\n\n \n\n\n\n In Proc. of the CoNLL 2007 Shared Task. Joint Conf. on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), June 2007. \n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Nivre2007,\n    title = {The CoNLL 2007 Shared Task on Dependency Parsing},\n    booktitle = {Proc. of the CoNLL 2007 Shared Task. Joint Conf. on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)},\n    year = {2007},\n    url = {/pub/conll07/overview3.pdf},\n    keywords = {parsing,dparse,ai.ku,NLP},\n    month = {June},\n    author = {Nivre, Joakim and Hall, Johan and K{\\"u}bler, Sandra and McDonald, Ryan and Nilsson, Jens and Riedel, Sebastian and Yuret, Deniz},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Verimli Düşünce Alışkanlıkları.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n In Eleştirel Düşünce Üzerine TUSIAD Raporu. TUSIAD, December 2007.\n \n\n\n\n
\n\n\n\n \n \n \"VerimliPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@incollection{Yuret2007tusiad,\n    author = {Yuret, Deniz},\n    title = {Verimli D{\\"u}\\c{s}{\\"u}nce Al{\\i}\\c{s}kanl{\\i}klar{\\i}},\n    booktitle = {Ele\\c{s}tirel D{\\"u}\\c{s}{\\"u}nce {\\"U}zerine TUSIAD Raporu},\n    publisher = {TUSIAD},\n    year = {2007},\n    month = {December},\n    url = {/research/2007/criticalthinking/criticalthinking.pdf},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n KU: Word Sense Disambiguation by Substitution.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), pages 207–214, Prague, Czech Republic, June 2007. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"KU:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yuret:2007:SemEval-2007,\n    author = {Yuret, Deniz},\n    title = {{KU}: Word Sense Disambiguation by Substitution},\n    booktitle = {Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007)},\n    month = {June},\n    year = {2007},\n    address = {Prague, Czech Republic},\n    publisher = {Association for Computational Linguistics},\n    pages = {207--214},\n    url = {http://www.aclweb.org/anthology/S/S07/S07-1044,/pub/semeval07/yuret-semeval07.pdf},\n    keywords = {semeval07.bib,WSD,acl08smoothing,SLM,cl09bib,ai.ku,scode,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n ngram-discount(7): Notes on the N-gram smoothing implementations in SRILM.\n \n \n \n \n\n\n \n Yuret, D.; and Stolcke, A.\n\n\n \n\n\n\n 2007.\n \n\n\n\n
\n\n\n\n \n \n \"ngram-discount(7):Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@manual{yuret2007ngram,\n    url = {http://www.speech.sri.com/projects/srilm/manpages/ngram-discount.7.html},\n    keywords = {comp542,SLM,NLP},\n    author = {Yuret, Deniz and Stolcke, Andreas},\n    year = {2007},\n    title = {ngram-discount(7): Notes on the N-gram smoothing implementations in SRILM},\n}\n\n
\n
\n\n\n\n
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\n\n
\n
\n  \n 2006\n \n \n (7)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Learning Morphological Disambiguation Rules for Turkish.\n \n \n \n \n\n\n \n Yuret, D.; and Türe, F.\n\n\n \n\n\n\n In HLT-NAACL 06, June 2006. \n \n\n\n\n
\n\n\n\n \n \n \"LearningPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret2006,\n    author = {Yuret, Deniz and T{\\"u}re, Ferhan},\n    title = {Learning Morphological Disambiguation Rules for Turkish},\n    year = {2006},\n    booktitle = {HLT-NAACL 06},\n    keywords = {ML,Morphology,ai.ku,NLP},\n    month = {June},\n    url = {https://aclweb.org/anthology/N/N06/N06-1042.pdf,/pub/hlt-naacl-06,/pub/hlt-naacl-06/morph-disamb.pdf,/pub/hlt-naacl-06/hlt06.ppt},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Secondary Structure Prediction Using Decision Lists.\n \n \n \n \n\n\n \n Yuret, D.; and Kurt, V.\n\n\n \n\n\n\n CCBB workshop presentation, September 2006.\n \n\n\n\n
\n\n\n\n \n \n \"SecondaryPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@misc{Yuret2006v,\n    author = {Yuret, Deniz and Kurt, Volkan},\n    title = {Secondary Structure Prediction Using Decision Lists},\n    year = {2006},\n    howpublished = {CCBB workshop presentation},\n    url = {/pub/ccbb06/secondary.ppt},\n    keywords = {Decision Lists,ai.ku,NLP},\n    month = {September},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Lexical attraction models of language.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n 2006.\n Revised version of my PhD work\n\n\n\n
\n\n\n\n \n \n \"LexicalPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@unpublished{Yuret2006u,\n    author = {Yuret, Deniz},\n    title = {Lexical attraction models of language},\n    year = {2006},\n    url = {/pub/lex-attr,/pub/lex-attr/lam-iscis06.pdf},\n    note = {Revised version of my PhD work},\n    keywords = {NLP,uparse,ai.ku},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Dependency Parsing as a Classification Problem.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n In Proceedings of the Tenth Conference on Computational Natural Language Learning (CoNLL-X), June 2006. \n \n\n\n\n
\n\n\n\n \n \n \"DependencyPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret2006c,\n    author = {Yuret, Deniz},\n    title = {Dependency Parsing as a Classification Problem},\n    year = {2006},\n    booktitle = {Proceedings of the Tenth Conference on Computational Natural Language Learning (CoNLL-X)},\n    url = {/pub/conll-06,/pub/conll-06/gpa-parser.pdf,/pub/conll-06/conll-x.ppt},\n    keywords = {dparse,parsing,ai.ku,NLP},\n    month = {June},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Clustering Word Pairs to Answer Analogy Questions.\n \n \n \n \n\n\n \n Biçici, E.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the Fifteenth Turkish Symposium on Artificial Intelligence and Neural Networks (TAINN 2006), June 2006. \n \n\n\n\n
\n\n\n\n \n \n \"ClusteringPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret2006d,\n    author = {Bi{\\c{c}}ici, Ergun and Yuret, Deniz},\n    title = {Clustering Word Pairs to Answer Analogy Questions},\n    year = {2006},\n    booktitle = {Proceedings of the Fifteenth Turkish Symposium on Artificial Intelligence and Neural Networks (TAINN 2006)},\n    url = {/pub/tainn-06,/pub/tainn-06/LAWSQ-LNCS.pdf},\n    month = {June},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n The Greedy Prepend Algorithm for Decision List Induction.\n \n \n \n \n\n\n \n Yuret, D.; and de la Maza, M.\n\n\n \n\n\n\n In Levi, A.; and others, editor(s), ISCIS 2006, LNCS 4263, pages 37–46, Berlin Heidelberg, November 2006. Springer-Verlag\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret2006a,\n    author = {Yuret, Deniz and de la Maza, Michael},\n    title = {The Greedy Prepend Algorithm for Decision List Induction},\n    year = {2006},\n    pages = {37--46},\n    editor = {Levi, A. and others},\n    address = {Berlin Heidelberg},\n    publisher = {Springer-Verlag},\n    url = {/pub/iscis06,/pub/iscis06/gpa-iscis06.pdf,/pub/iscis06/iscis06.ppt},\n    keywords = {Decision Lists,ai.ku,NLP},\n    month = {November},\n    booktitle = {ISCIS 2006, LNCS 4263},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Quantum Mechanical Calculations of Tryptophan and Comparison with Conformations in Native Proteins.\n \n \n \n \n\n\n \n Yurtsever, E.; Yuret, D.; and Erman, B.\n\n\n \n\n\n\n J. Phys. Chem. A, 110(51): 13933–13938. December 2006.\n \n\n\n\n
\n\n\n\n \n \n \"QuantumPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{Yuret2006jpc,\n    title = {Quantum Mechanical Calculations of Tryptophan and Comparison with Conformations in Native Proteins},\n    journal = {J. Phys. Chem. A},\n    year = {2006},\n    author = {Yurtsever, Ersin and Yuret, Deniz and Erman, Burak},\n    url = {http://dx.doi.org/10.1021/jp062921n},\n    month = {December},\n    volume = {110},\n    number = {51},\n    pages = {13933--13938},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
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\n
\n  \n 2005\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Method of utilizing implicit references to answer a query.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n US Patent Number 6957213, Oct 2005.\n \n\n\n\n
\n\n\n\n \n \n \"MethodPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@misc{yuret2005pat,\n    url = {http://patft.uspto.gov/netacgi/nph-Parser?Sect2=PTO1&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&d=PALL&RefSrch=yes&Query=PN%2F6957213,pub/uspto6957213/Method_of_utilizing_implicit_references_.pdf},\n    author = {Yuret, Deniz},\n    title = {Method of utilizing implicit references to answer a query},\n    howpublished = {US Patent Number 6957213},\n    month = {Oct},\n    year = {2005},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
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\n  \n 2004\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Relationships Between Amino Acid Sequence and Backbone Torsion Angle Preferences.\n \n \n \n \n\n\n \n Keskin, Ö.; Yuret, D.; Gürsoy, A.; Türkay, M.; and Erman, B.\n\n\n \n\n\n\n Proteins: Structure, Function, and Bioinformatics, 55(4): 992–998. June 2004.\n \n\n\n\n
\n\n\n\n \n \n \"RelationshipsPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{Keskin2004,\n    title = {Relationships Between Amino Acid Sequence and Backbone Torsion Angle Preferences},\n    year = {2004},\n    journal = {Proteins: Structure, Function, and Bioinformatics},\n    volume = {55},\n    number = {4},\n    pages = {992--998},\n    url = {/pub/psfg04.html,/pub/psfg04.pdf},\n    author = {Keskin, {\\"O}zlem and Yuret, Deniz and G{\\"u}rsoy, Attila and T{\\"u}rkay, Metin and Erman, Burak},\n    month = {June},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Some experiments with a Naive Bayes WSD system.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n In Mihalcea, R.; and ssss, editor(s), Senseval-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text, pages 265–268, Barcelona, Spain, July 2004. Association for Computational Linguistics\n \n\n\n\n
\n\n\n\n \n \n \"SomePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yuret:2004:Senseval-3,\n    author = {Yuret, Deniz},\n    title = {Some experiments with a {N}aive {B}ayes {WSD} system},\n    booktitle = {Senseval-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text},\n    editor = {Rada Mihalcea and ssss},\n    year = {2004},\n    month = {July},\n    address = {Barcelona, Spain},\n    publisher = {Association for Computational Linguistics},\n    pages = {265--268},\n    keywords = {WSD,semeval07.bib,cl09bib,ai.ku,NLP},\n    url = {/pub/senseval3.html,/pub/senseval3.pdf,/pub/senseval3.ps.gz},\n}\n\n
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\n  \n 2002\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Alpha-beta-conspiracy search.\n \n \n \n \n\n\n \n McAllester, D. A.; and Yuret, D.\n\n\n \n\n\n\n ICGA Journal, 25(1): 16–35. 2002.\n \n\n\n\n
\n\n\n\n \n \n \"Alpha-beta-conspiracyPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@article{McAllester2002,\n    author = {McAllester, David Allen and Yuret, Deniz},\n    title = {Alpha-beta-conspiracy search},\n    year = {2002},\n    journal = {ICGA Journal},\n    volume = {25},\n    pages = {16--35},\n    keywords = {AI,ai.ku,NLP},\n    number = {1},\n    url = {/pub/abc93.html,/pub/abc93.ps.gz,/bib/mcallester/McAllester2002/abc02.pdf},\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Omnibase: Uniform access to heterogeneous data for question answering.\n \n \n \n \n\n\n \n Katz, B.; Felshin, S.; Yuret, D.; and others\n\n\n \n\n\n\n In NLDB 2002, LNCS 2553, pages 230–234. Springer-Verlag, 2002.\n \n\n\n\n
\n\n\n\n \n \n \"Omnibase:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@incollection{Katz2002,\n    author = {Katz, Boris and Felshin, Sue and Yuret, Deniz and others},\n    title = {Omnibase: Uniform access to heterogeneous data for question answering},\n    year = {2002},\n    pages = {230--234},\n    publisher = {Springer-Verlag},\n    url = {/pub/nldb02,/pub/nldb02/Katz-etal-NLDB02.pdf},\n    booktitle = {NLDB 2002, LNCS 2553},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n
\n  \n 1999\n \n \n (3)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Modeling the Economics of Internet Companies.\n \n \n \n \n\n\n \n Oğuş, A.; de la Maza, M.; and Yuret, D.\n\n\n \n\n\n\n In Computing in Economics and Finance, Proceedings of the Fifth International Conference of the Society for Computational Economics, 1999. \n \n\n\n\n
\n\n\n\n \n \n \"ModelingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Ogus1999,\n    title = {Modeling the Economics of Internet Companies},\n    year = {1999},\n    booktitle = {Computing in Economics and Finance, Proceedings of the Fifth International Conference of the Society for Computational Economics},\n    url = {/pub/cef99.html,/pub/cef99.pdf,/pub/cef99.ps.gz},\n    author = {O{\\u{g}}u{\\c{s}}, Ayla and de la Maza, Michael and Yuret, Deniz},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
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\n \n\n \n \n \n \n \n \n Word sense disambiguation for information retrieval.\n \n \n \n \n\n\n \n Uzuner, Ö.; Katz, B.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the 1999 16th National Conference on Artificial Intelligence (AAAI-99), 1999. \n \n\n\n\n
\n\n\n\n \n \n \"WordPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Uzuner1999,\n    title = {Word sense disambiguation for information retrieval},\n    year = {1999},\n    booktitle = {Proceedings of the 1999 16th National Conference on Artificial Intelligence (AAAI-99)},\n    url = {/pub/aaai99.html,/pub/aaai99.pdf},\n    keywords = {NLP,WSD,ai.ku},\n    author = {Uzuner, {\\"O}zlem and Katz, Boris and Yuret, Deniz},\n}\n\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Integrating web resources and lexicons into a natural language query system.\n \n \n \n \n\n\n \n Katz, B.; Yuret, D.; and others\n\n\n \n\n\n\n In Proceedings of the 6th IEEE International Conference on Multimedia Computing and Systems (IEEE ICMCS'99), 1999. \n \n\n\n\n
\n\n\n\n \n \n \"IntegratingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Katz1999,\n    author = {Katz, Boris and Yuret, Deniz and others},\n    title = {Integrating web resources and lexicons into a natural language query system},\n    year = {1999},\n    booktitle = {Proceedings of the 6th IEEE International Conference on Multimedia Computing and Systems (IEEE ICMCS'99)},\n    url = {/pub/icmcs99.html,/pub/icmcs99.ps.gz},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n  \n 1998\n \n \n (3)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Blitz: a preprocessor for detecting context-independent linguistic structures.\n \n \n \n \n\n\n \n Katz, B.; Yuret, D.; and others\n\n\n \n\n\n\n In Proceedings of the 5th Pacific Rim International Conference on Artificial Intelligence (PRICAI '98), 1998. \n \n\n\n\n
\n\n\n\n \n \n \"Blitz:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Katz1998,\n    author = {Katz, Boris and Yuret, Deniz and others},\n    title = {Blitz: a preprocessor for detecting context-independent linguistic structures},\n    year = {1998},\n    booktitle = {Proceedings of the 5th Pacific Rim International Conference on Artificial Intelligence (PRICAI '98)},\n    url = {/pub/pricai98.html,/pub/pricai98.doc},\n    keywords = {NLP,ai.ku},\n}\n\n
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\n \n\n \n \n \n \n \n \n Discovery of linguistic relations using lexical attraction.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n Ph.D. Thesis, MIT, 1998.\n \n\n\n\n
\n\n\n\n \n \n \"DiscoveryPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@phdthesis{Yuret1998,\n    author = {Yuret, Deniz},\n    title = {Discovery of linguistic relations using lexical attraction},\n    year = {1998},\n    school = {MIT},\n    url = {/pub/yuretphd.html,/pub/yuretphd.pdf,/pub/yuretphd.ps.gz},\n    keywords = {NLP,uparse,ai.ku},\n}\n\n
\n
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\n\n\n
\n \n\n \n \n \n \n \n \n How do firms transition between monopoly and competitive behavior? An Agent-based Economic Model.\n \n \n \n \n\n\n \n de la Maza, M.; Oğuş, A.; and Yuret, D.\n\n\n \n\n\n\n In Proceedings of the Sixth International Conference on Artificial Life, 1998. \n \n\n\n\n
\n\n\n\n \n \n \"HowPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret1998_1,\n    year = {1998},\n    booktitle = {Proceedings of the Sixth International Conference on Artificial Life},\n    url = {/pub/alife98.html,/pub/alife98.ps.gz},\n    author = {de la Maza, Michael and O{\\u{g}}u{\\c{s}}, Ayla and Yuret, Deniz},\n    keywords = {ai.ku,NLP},\n    title = {How do firms transition between monopoly and competitive behavior? {An} Agent-based Economic Model.},\n}\n\n
\n
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\n
\n  \n 1996\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n The binding roots of symbolic AI: a brief review of the Cyc project.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n 1996.\n Area exam paper\n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@unpublished{Yuret1996,\n    author = {Yuret, Deniz},\n    title = {The binding roots of symbolic AI: a brief review of the Cyc project},\n    year = {1996},\n    url = {/pub/cyc96.html,/pub/cyc96.ps.gz},\n    keywords = {AI,ai.ku,NLP},\n    note = {Area exam paper},\n}\n\n
\n
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\n
\n  \n 1995\n \n \n (4)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n A brief review of memory research in cognitive neuroscience.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n 1995.\n Working Paper 343, MIT AI Laboratory\n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@unpublished{Yuret1995,\n    author = {Yuret, Deniz},\n    title = {A brief review of memory research in cognitive neuroscience},\n    year = {1995},\n    url = {/pub/aiwp343.html,/pub/aiwp343.ps.gz},\n    keywords = {COG,ai.ku,NLP},\n    note = {Working Paper 343, MIT AI Laboratory},\n}\n\n
\n
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\n\n\n
\n \n\n \n \n \n \n \n \n Seeing clearly: Medical imaging now and tomorrow.\n \n \n \n \n\n\n \n de la Maza, M.; and Yuret, D.\n\n\n \n\n\n\n In Pickover, C. A., editor(s), Future Health: Computers and Medicine in the 21st Century. St. Martin's Press, 1995.\n \n\n\n\n
\n\n\n\n \n \n \"SeeingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@incollection{Yuret1995_1,\n    author = {de la Maza, Michael and Yuret, Deniz},\n    title = {Seeing clearly: Medical imaging now and tomorrow},\n    year = {1995},\n    booktitle = {Future Health: Computers and Medicine in the 21st Century},\n    editor = {Pickover, Clifford A.},\n    publisher = {St. Martin's Press},\n    url = {/pub/aimed95.html,/pub/aimed95.ps.gz},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n A model of stock market participants.\n \n \n \n \n\n\n \n de la Maza, M.; and Yuret, D.\n\n\n \n\n\n\n In Biethahn, J.; and Nissen, V., editor(s), Evolutionary Algorithms in Management Applications. Springer, 1995.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@incollection{Yuret1995_2,\n    author = {de la Maza, Michael and Yuret, Deniz},\n    title = {A model of stock market participants},\n    year = {1995},\n    booktitle = {Evolutionary Algorithms in Management Applications},\n    editor = {Biethahn, J{\\"o}rg and Nissen, Volker},\n    publisher = {Springer},\n    url = {/pub/aimng95.html,/pub/aimng95.ps.gz},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Neural network applications: A critique.\n \n \n \n \n\n\n \n de la Maza, M.; and Yuret, D.\n\n\n \n\n\n\n The Magazine of Artificial Intelligence in Finance, 2(1). 1995.\n \n\n\n\n
\n\n\n\n \n \n \"NeuralPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{Yuret1995_3,\n    author = {de la Maza, Michael and Yuret, Deniz},\n    title = {Neural network applications: A critique},\n    year = {1995},\n    journal = {The Magazine of Artificial Intelligence in Finance},\n    volume = {2},\n    number = {1},\n    url = {/pub/aifin95.html,/pub/aifin95.ps.gz},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
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\n
\n  \n 1994\n \n \n (6)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n The principle of pressure in chess.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n In The Third Turkish Symposium on Artificial Intelligence and Neural Networks (TAINN '94), 1994. \n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret1994chess,\n    author = {Yuret, Deniz},\n    title = {The principle of pressure in chess},\n    year = {1994},\n    booktitle = {The Third Turkish Symposium on Artificial Intelligence and Neural Networks (TAINN '94)},\n    url = {/pub/tainn94.html,/pub/tainn94.ps.gz},\n    keywords = {AI,ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n From genetic algorithms to efficient optimization.\n \n \n \n \n\n\n \n Yuret, D.\n\n\n \n\n\n\n Technical Report 1569, MIT AI Laboratory, 1994.\n \n\n\n\n
\n\n\n\n \n \n \"FromPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n
\n 
@techreport{Yuret1994,\n    author = {Yuret, Deniz},\n    title = {From genetic algorithms to efficient optimization},\n    year = {1994},\n    number = {1569},\n    institution = {MIT AI Laboratory},\n    url = {/pub/aitr1569.html,/pub/aitr1569.ps.gz},\n    keywords = {AI,acl08smoothing,SLM,ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Dynamic hill climbing.\n \n \n \n \n\n\n \n de la Maza, M.; and Yuret, D.\n\n\n \n\n\n\n AI Expert. 1994.\n \n\n\n\n
\n\n\n\n \n \n \"DynamicPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{Yuret1994c,\n    author = {de la Maza, Michael and Yuret, Deniz},\n    title = {Dynamic hill climbing},\n    year = {1994},\n    journal = {AI Expert},\n    url = {/pub/aiexp94.html,/pub/aiexp94.ps.gz},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n A futures market simulation with non-rational participants.\n \n \n \n \n\n\n \n de la Maza, M.; and Yuret, D.\n\n\n \n\n\n\n In Brooks, R. A.; and Maes, P., editor(s), Proceedings of the Fourth International Workshop on the Synthesis and Simulation of Living Systems, 1994. \n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret1994_2,\n    author = {de la Maza, Michael and Yuret, Deniz},\n    title = {A futures market simulation with non-rational participants},\n    year = {1994},\n    booktitle = {Proceedings of the Fourth International Workshop on the Synthesis and Simulation of Living Systems},\n    editor = {Brooks, Rodney Allen and Maes, Pattie},\n    url = {/pub/alife94.html,/pub/alife94.ps.gz},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n A genetic algorithm system for predicting the OEX.\n \n \n \n \n\n\n \n Yuret, D.; and de la Maza, M.\n\n\n \n\n\n\n Technical Analysis of Stocks and Commodities. 1994.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{Yuret1994_3,\n    author = {Yuret, Deniz and de la Maza, Michael},\n    year = {1994},\n    journal = {Technical Analysis of Stocks and Commodities},\n    url = {/pub/tasc94.html,/pub/tasc94.ps.gz},\n    keywords = {ai.ku,NLP},\n    title = {A genetic algorithm system for predicting the {OEX}},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Experimenting with a market simulation.\n \n \n \n \n\n\n \n de la Maza, M.; and Yuret, D.\n\n\n \n\n\n\n The Magazine of Artificial Intelligence in Finance, 1(3). 1994.\n \n\n\n\n
\n\n\n\n \n \n \"ExperimentingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{Yuret1994_4,\n    author = {de la Maza, Michael and Yuret, Deniz},\n    title = {Experimenting with a market simulation},\n    year = {1994},\n    journal = {The Magazine of Artificial Intelligence in Finance},\n    volume = {1},\n    number = {3},\n    url = {/pub/aifin94.html,/pub/aifin94.ps.gz},\n    keywords = {ai.ku,NLP},\n}\n\n
\n
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\n
\n  \n 1993\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Dynamic hill climbing: Overcoming the limitations of optimization techniques.\n \n \n \n \n\n\n \n Yuret, D.; and de la Maza, M.\n\n\n \n\n\n\n In The Second Turkish Symposium on Artificial Intelligence and Neural Networks, 1993. \n \n\n\n\n
\n\n\n\n \n \n \"DynamicPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret1993_2,\n    author = {Yuret, Deniz and de la Maza, Michael},\n    title = {Dynamic hill climbing: Overcoming the limitations of optimization techniques},\n    year = {1993},\n    booktitle = {The Second Turkish Symposium on Artificial Intelligence and Neural Networks},\n    url = {/pub/tainn93.html,/pub/tainn93.ps.gz},\n    keywords = {ai.ku,NLP},\n}\n\n
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\n
\n  \n 1900\n \n \n (6)\n \n \n
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\n \n\n \n \n \n \n \n \n Agglomerative Word Ordering Algorithm for Sentence Generation.\n \n \n \n \n\n\n \n Han, A.; and Yuret, D.\n\n\n \n\n\n\n In EACL-2014, 1900. \n (rejected)\n\n\n\n
\n\n\n\n \n \n \"AgglomerativePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{han2014ordering,\n    author = {Han, Aydin and Yuret, Deniz},\n    title = {Agglomerative Word Ordering Algorithm for Sentence Generation},\n    keywords = {ai.ku,NLP},\n    url = {/bib/han/han2013ordering/unshuffling.pdf},\n    year = {1900},\n    note = {(rejected)},\n    booktitle = {EACL-2014},\n}\n\n
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\n \n\n \n \n \n \n \n Parsing using context vectors.\n \n \n \n\n\n \n Yuret, D.; Sensoy, H.; and Cirik, V.\n\n\n \n\n\n\n In ?, 1900. \n (in preparation)\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{yuret2016parsing,\n    keywords = {ai.ku,NLP},\n    note = {(in preparation)},\n    author = {Yuret, Deniz and Sensoy, Husnu and Cirik, Volkan},\n    title = {Parsing using context vectors},\n    booktitle = {?},\n    year = {1900},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Recognizing Lexical Entailment using Substitutability.\n \n \n \n\n\n \n Kuru, O.; and Yuret, D.\n\n\n \n\n\n\n ?. 1900.\n (in preparation)\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{kuru2016rle,\n    keywords = {ai.ku,NLP},\n    author = {Kuru, Onur and Yuret, Deniz},\n    title = {Recognizing Lexical Entailment using Substitutability},\n    journal = {?},\n    note = {(in preparation)},\n    year = {1900},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Semantic parsing.\n \n \n \n\n\n \n Baran, C.; and Yuret, D.\n\n\n \n\n\n\n TACL. December 1900.\n (in preparation)\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@article{baran2014semparse,\n    author = {Baran, Cihan and Yuret, Deniz},\n    title = {Semantic parsing},\n    journal = {TACL},\n    keywords = {ai.ku,NLP},\n    note = {(in preparation)},\n    month = {December},\n    year = {1900},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Context Vectors using Substitute Word Distributions.\n \n \n \n\n\n \n Cirik, V.; Morency, L.; and Yuret, D.\n\n\n \n\n\n\n In ?, 1900. \n (in preparation)\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{Yuret2016context,\n    keywords = {ai.ku,NLP},\n    title = {Context Vectors using Substitute Word Distributions},\n    author = {Cirik, Volkan and Morency, Louis-Philippe and Yuret, Deniz},\n    booktitle = {?},\n    note = {(in preparation)},\n    year = {1900},\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Action Grounded Natural Language Generation.\n \n \n \n\n\n \n Bisk, Y.; Konstas, Y.; Can, O. A.; Yuret, D.; and Marcu, D.\n\n\n \n\n\n\n In ?, 1900. \n (in preparation)\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
\n 
@inproceedings{bisk2016generation,\n    title = {Action Grounded Natural Language Generation},\n    keywords = {ai.ku,NLP},\n    note = {(in preparation)},\n    author = {Bisk, Yonatan and Konstas, Yannis and Can, Ozan Arkan and Yuret, Deniz and Marcu, Daniel},\n    booktitle = {?},\n    year = {1900},\n}\n\n
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\n
\n  \n undefined\n \n \n (2)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n Emotion Dependent Domain Adaptation for Speech Driven Affective Facial Feature Synthesis.\n \n \n \n\n\n \n Sadiq, R.; and Erzin, E.\n\n\n \n\n\n\n IEEE Transactions on Affective Computing. .\n \n\n\n\n
\n\n\n\n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{9140332,\n    author = {Sadiq, Rizwan and Erzin, Engin},\n    journal = {IEEE Transactions on Affective Computing},\n    title = {Emotion Dependent Domain Adaptation for Speech Driven Affective Facial Feature Synthesis},\n    doi = {10.1109/TAFFC.2020.3008456}}
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\n \n\n \n \n \n \n \n .\n \n \n \n\n\n \n ..\n\n\n \n\n\n\n . .\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{..,\n    author = {..},\n}\n\n
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\n  \n 2015–2018\n \n \n (2)\n \n \n
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\n \n \n
\n \n\n \n \n \n \n \n Relational symbol grounding through affordance learning (ReGROUND).\n \n \n \n\n\n \n De Raedt, L.; Yuret, D.; and Saffiotti, A.\n\n\n \n\n\n\n CHIST-ERA Project on Human Language Understanding: Grounding Language Learning, 2015–2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@misc{215E201,\n    author = {De Raedt, Luc and Yuret, Deniz and Saffiotti, Alessandro},\n    howpublished = {CHIST-ERA Project on Human Language Understanding: Grounding Language Learning},\n    year = {2015--2018},\n    title = {Relational symbol grounding through affordance learning ({ReGROUND})},\n    keywords = {NLP},\n}\n\n
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\n \n\n \n \n \n \n \n Dilbilimsel ve Görsel İpuçlarını Birlikte Kullanarak Gezinim Dilinin Öğrenilmesi.\n \n \n \n\n\n \n Yemez, Y.; and Yuret, D.\n\n\n \n\n\n\n TÜBİTAK 1001 Project, 2015–2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
\n 
@misc{114E628,\n    author = {Yemez, Y\\"ucel and Yuret, Deniz},\n    title = {Dilbilimsel ve G{\\"o}rsel {\\.I}pu{\\c{c}}lar{\\i}n{\\i} Birlikte Kullanarak Gezinim Dilinin {\\"O}{\\u{g}}renilmesi},\n    howpublished = {T\\"UB\\.ITAK 1001 Project},\n    year = {2015--2018},\n    keywords = {NLP},\n}\n\n
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