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\n \n \n Fix it now\n

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\n \n \n

\n \n 2024\n \n \n (4)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n DSD$^2$: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?.\n \n \n \n \n\n\n \n Qu'etu, V.; and Tartaglione, E.\n\n\n \n\n\n\n In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024). AAAI Press, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"DSD$^2$:$ Paper\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

@inproceedings{quetu2024dsd2,\n  title={DSD$^2$: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?},\n  author={Qu{\\&#x27;e}tu, Victor and Tartaglione, Enzo},\n  booktitle={Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024). AAAI Press},\n  year={2024},\n  url={https://arxiv.org/abs/2303.01213.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Find the Lady: Permutation and Re-Synchronization of Deep Neural Networks.\n \n \n \n \n\n\n \n De Sousa Trias, C.; Mitrea, M.; Fiandrotti, A.; Cagnazzo, M.; Chaudhuri, S.; and Tartaglione, E.\n\n\n \n\n\n\n In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024). AAAI Press, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"Find$ 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

@inproceedings{desousa2024find,\n  title={Find the Lady: Permutation and Re-Synchronization of Deep Neural Networks},\n  author={De Sousa Trias, Carl and Mitrea, Mihai and Fiandrotti, Attilio and Cagnazzo, Marco and Chaudhuri, Sumanta and Tartaglione, Enzo},\n  booktitle={Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024). AAAI Press},\n  year={2024},\n  url={https://arxiv.org/abs/2312.14182.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Mini but Mighty: Finetuning ViTs with Mini Adapters.\n \n \n \n \n\n\n \n Marouf, I. E.; Tartaglione, E.; and Lathuili`ere, S.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pages 1732–1741, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"Mini$ 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

@inproceedings{marouf2024mini,\n  title={Mini but Mighty: Finetuning ViTs with Mini Adapters},\n  author={Marouf, Imad Eddine and Tartaglione, Enzo and Lathuili{\\&#x60;e}re, St{\\&#x27;e}phane},\n  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},\n  pages={1732--1741},\n  year={2024},\n  url={https://openaccess.thecvf.com/content/WACV2024/papers/Marouf_Mini_but_Mighty_Finetuning_ViTs_With_Mini_Adapters_WACV_2024_paper.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Towards On-device Learning on the Edge: Ways to Select Neurons to Update under a Budget Constraint.\n \n \n \n \n\n\n \n Qu'elennec, A.; Tartaglione, E.; Mozharovskyi, P.; and Nguyen, V.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pages 685–694, 2024. \n \n\n\n\n
\n\n\n\n \n \n $\"Towards$ Paper\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

@inproceedings{quelennec2024towards,\n  title={Towards On-device Learning on the Edge: Ways to Select Neurons to Update under a Budget Constraint},\n  author={Qu{\\&#x27;e}lennec, A{\\&quot;e}l and Tartaglione, Enzo and Mozharovskyi, Pavlo and Nguyen, Van-Tam},\n  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},\n  pages={685--694},\n  year={2024},\n  url={https://openaccess.thecvf.com/content/WACV2024W/SCIoT/papers/Quelennec_Towards_On-Device_Learning_on_the_Edge_Ways_To_Select_Neurons_WACVW_2024_paper.pdf}\n}\n

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\n \n 2023\n \n \n (20)\n \n \n

\n \n \n

\n \n\n \n \n \n \n \n \n Unified Measures for the Rate-Distortion-Latency Trade-off.\n \n \n \n \n\n\n \n Vijayaratnam, M.; Milovanovic, M.; Cagnazzo, M.; Tartaglione, E.; and Valenzise, G.\n\n\n \n\n\n\n In IEEE International Conference on Visual Communications and Image Processing, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Unified$ 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

@inproceedings{vijayaratnam2023unified,\n  title={Unified Measures for the Rate-Distortion-Latency Trade-off},\n  author={Vijayaratnam, Melan and Milovanovic, Marta and Cagnazzo, Marco and Tartaglione, Enzo and Valenzise, Giuseppe},\n  booktitle={IEEE International Conference on Visual Communications and Image Processing},\n  year={2023},\n  url={https://centralesupelec.hal.science/hal-04350236/file/VCIP_2023_Melan_final_camera_ready.pdf}\n}\n

\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Differentiable Entropy Model for Learned Image Compression.\n \n \n \n \n\n\n \n Presta, A.; Fiandrotti, A.; Tartaglione, E.; and Grangetto, M.\n\n\n \n\n\n\n In International Conference on Image Analysis and Processing, pages 328–339, 2023. Springer\n \n\n\n\n
\n\n\n\n \n \n $\"A$ 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

@inproceedings{presta2023differentiable,\n  title={A Differentiable Entropy Model for Learned Image Compression},\n  author={Presta, Alberto and Fiandrotti, Attilio and Tartaglione, Enzo and Grangetto, Marco},\n  booktitle={International Conference on Image Analysis and Processing},\n  pages={328--339},\n  year={2023},\n  url={https://link.springer.com/chapter/10.1007/978-3-031-43148-7_28},\n  organization={Springer}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Two is Better than One: Achieving High-Quality 3D Scene Modeling with a NeRF Ensemble.\n \n \n \n \n\n\n \n Di Sario, F.; Renzulli, R.; Tartaglione, E.; and Grangetto, M.\n\n\n \n\n\n\n In International Conference on Image Analysis and Processing, pages 320–331, 2023. Springer\n \n\n\n\n
\n\n\n\n \n \n $\"Two$ 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

@inproceedings{di2023two,\n  title={Two is Better than One: Achieving High-Quality 3D Scene Modeling with a NeRF Ensemble},\n  author={Di Sario, Francesco and Renzulli, Riccardo and Tartaglione, Enzo and Grangetto, Marco},\n  booktitle={International Conference on Image Analysis and Processing},\n  pages={320--331},\n  year={2023},\n  url={https://telecom-paris.hal.science/hal-04205640/file/ICIAP23_EnsembleNeRF-2.pdf},\n  organization={Springer}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Sparse Double Descent in Vision Transformers: real or phantom threat?.\n \n \n \n \n\n\n \n Qu'etu, V.; Milovanovi'c, M.; and Tartaglione, E.\n\n\n \n\n\n\n In International Conference on Image Analysis and Processing, pages 490–502, 2023. Springer\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

@inproceedings{quetu2023sparse,\n  title={Sparse Double Descent in Vision Transformers: real or phantom threat?},\n  author={Qu{\\&#x27;e}tu, Victor and Milovanovi{\\&#x27;c}, Marta and Tartaglione, Enzo},\n  booktitle={International Conference on Image Analysis and Processing},\n  pages={490--502},\n  year={2023},\n  url={https://arxiv.org/pdf/2307.14253},\n  organization={Springer}\n}\n\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Disentangling private classes through regularization.\n \n \n \n \n\n\n \n Tartaglione, E.; Gennari, F.; Quétu, V.; and Grangetto, M.\n\n\n \n\n\n\n Neurocomputing,126612. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Disentangling$ 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 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

@article{TARTAGLIONE2023126612,\ntitle = {Disentangling private classes through regularization},\njournal = {Neurocomputing},\npages = {126612},\nyear = {2023},\nissn = {0925-2312},\ndoi = {https://doi.org/10.1016/j.neucom.2023.126612},\nurl = {https://www.sciencedirect.com/science/article/pii/S092523122300735X},\nauthor = {Enzo Tartaglione and Francesca Gennari and Victor Quétu and Marco Grangetto},\nkeywords = {Deep learning, GDPR, Regularization, Disentangling, Artificial neural networks, Private classes}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Mining bias-target Alignment from Voronoi Cells.\n \n \n \n \n\n\n \n Nahon, R.; Nguyen, V.; and Tartaglione, E.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pages 4946-4955, October 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Mining$ 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

@InProceedings{Nahon_2023_ICCV,\n    author    = {Nahon, R\\&#x27;emi and Nguyen, Van-Tam and Tartaglione, Enzo},\n    title     = {Mining bias-target Alignment from Voronoi Cells},\n    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},\n    month     = {October},\n    year      = {2023},\n    pages     = {4946-4955},\n    url={https://openaccess.thecvf.com/content/ICCV2023/papers/Nahon_Mining_bias-target_Alignment_from_Voronoi_Cells_ICCV_2023_paper.pdf}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Shannon strikes again! entropy-based pruning in deep neural networks for transfer learning under extreme memory and computation budgets.\n \n \n \n \n\n\n \n Spadaro, G.; Renzulli, R.; Bragagnolo, A.; Giraldo, J. H; Fiandrotti, A.; Grangetto, M.; and Tartaglione, E.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 1518–1522, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Shannon$ 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

@inproceedings{spadaro2023shannon,\n  title={Shannon strikes again! entropy-based pruning in deep neural networks for transfer learning under extreme memory and computation budgets},\n  author={Spadaro, Gabriele and Renzulli, Riccardo and Bragagnolo, Andrea and Giraldo, Jhony H and Fiandrotti, Attilio and Grangetto, Marco and Tartaglione, Enzo},\n  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},\n  pages={1518--1522},\n  year={2023},\n  url={https://openaccess.thecvf.com/content/ICCV2023W/RCV/papers/Spadaro_Shannon_Strikes_Again_Entropy-Based_Pruning_in_Deep_Neural_Networks_for_ICCVW_2023_paper.pdf}\n}\n

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\n\n\n

\n \n\n \n \n \n \n \n \n SCoTTi: Save Computation at Training Time with an adaptive framework.\n \n \n \n \n\n\n \n Li, Z.; Tartaglione, E.; and Nguyen, V.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 1443–1452, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"SCoTTi:$ 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

@inproceedings{li2023scotti,\n  title={SCoTTi: Save Computation at Training Time with an adaptive framework},\n  author={Li, Ziyu and Tartaglione, Enzo and Nguyen, Van-Tam},\n  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},\n  pages={1443--1452},\n  year={2023},\n  url={https://openaccess.thecvf.com/content/ICCV2023W/RCV/papers/Li_SCoTTi_Save_Computation_at_Training_Time_with_an_Adaptive_Framework_ICCVW_2023_paper.pdf}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Can Unstructured Pruning Reduce the Depth in Deep Neural Networks?.\n \n \n \n \n\n\n \n Liao, Z.; Qu'etu, V.; Nguyen, V.; and Tartaglione, E.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 1402–1406, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Can$ 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

@inproceedings{liao2023can,\n  title={Can Unstructured Pruning Reduce the Depth in Deep Neural Networks?},\n  author={Liao, Zhu and Qu{\\&#x27;e}tu, Victor and Nguyen, Van-Tam and Tartaglione, Enzo},\n  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},\n  pages={1402--1406},\n  year={2023},\n  url={https://openaccess.thecvf.com/content/ICCV2023W/RCV/papers/Liao_Can_Unstructured_Pruning_Reduce_the_Depth_in_Deep_Neural_Networks_ICCVW_2023_paper.pdf}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n A hitchhiker's guide to white-box neural network watermarking robustness.\n \n \n \n\n\n \n De Sousa Trias, C.; Mitrea, M.; Tartaglione, E.; Fiandrotti, A.; Cagnazzo, M.; and Chaudhuri, S.\n\n\n \n\n\n\n In European Workshop on Visual Information Processing, 2023. \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

@inproceedings{dsousa,\n  title={A hitchhiker&#x27;s guide to white-box neural network watermarking robustness},\n  author={De Sousa Trias, Carl and Mitrea, Mihai and Tartaglione, Enzo and Fiandrotti, Attilio and Cagnazzo, Marco and Chaudhuri, Sumanta},\n  booktitle={European Workshop on Visual Information Processing},\n  year={2023}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n All predictions matter: an online video prediction approach.\n \n \n \n\n\n \n Vijayaratnam, M.; Valenzise, G.; Tartaglione, E.; and Cagnazzo, M.\n\n\n \n\n\n\n In European Workshop on Visual Information Processing, 2023. \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

@inproceedings{nahon2023mining,\n  title={All predictions matter: an online video prediction approach},\n  author={Vijayaratnam, Melan and Valenzise, Giuseppe and Tartaglione, Enzo and Cagnazzo, Marco},\n  booktitle={European Workshop on Visual Information Processing},\n  year={2023}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n Mental state classification using EEG signals: ethics, law and challenges.\n \n \n \n\n\n \n Nahon, R.; Bagheri, N.; Varni, G.; Tartaglione, E.; and Nguyen, V.\n\n\n \n\n\n\n In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery - workshop track, 2023. \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

@inproceedings{nahon2023mining,\n  title={Mental state classification using EEG signals: ethics, law and challenges},\n  author={Nahon, R{\\&#x27;e}mi and Bagheri, Nasim and Varni, Giovanna and Tartaglione, Enzo and Nguyen, Van-Tam},\n  booktitle={European Conference on Machine Learning and Principles and Practice of Knowledge Discovery - workshop track},\n  year={2023}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Learn how to Prune Pixels for Multi-view Neural Image-based Synthesis.\n \n \n \n \n\n\n \n Milovanovi'c, M.; Tartaglione, E.; Cagnazzo, M.; and Henry, F.\n\n\n \n\n\n\n In IEEE International Cnference on Multimedia and Expo - Immersive Media Compression Workshop, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Learn$ 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

@inproceedings{milovanovic2023learn,\n  title={Learn how to Prune Pixels for Multi-view Neural Image-based Synthesis},\n  author={Milovanovi{\\&#x27;c}, Marta and Tartaglione, Enzo and Cagnazzo, Marco and Henry, F{\\&#x27;e}lix},\n  booktitle={IEEE International Cnference on Multimedia and Expo - Immersive Media Compression Workshop},\n  year={2023},\n  url={https://arxiv.org/pdf/2305.03572}\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Can we avoid Double Descent in Deep Neural Networks?.\n \n \n \n \n\n\n \n Qu'etu, V.; and Tartaglione, E.\n\n\n \n\n\n\n In 2023 IEEE International Conference on Image Processing (ICIP), 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Can$ 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

@inproceedings{quetu2023dodginge,\n  title={Can we avoid Double Descent in Deep Neural Networks?},\n  author={Qu{\\&#x27;e}tu, Victor and Tartaglione, Enzo},\n  booktitle={2023 IEEE International Conference on Image Processing (ICIP)}, \n  year={2023},\n  url={https://arxiv.org/pdf/2302.13259}\n}\n

\n\n\n\n

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\n \n\n \n \n \n \n \n AIoT-based Neural Decoding and Neurofeedback for Accelerated Cognitive Training: Vision, Directions and Preliminary Results .\n \n \n \n\n\n \n Nguyen, V.; Tartaglione, E.; and Dinh, T.\n\n\n \n\n\n\n In 22nd IEEE Statistical Signal Processing Workshop, 2023. \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

@inproceedings{wang2023optimized,\n  title={AIoT-based Neural Decoding and Neurofeedback for Accelerated Cognitive Training: Vision, Directions and Preliminary Results\n},\n  author={Nguyen, Van-Tam and Tartaglione, Enzo and Dinh, Tuan},\n  booktitle={22nd IEEE Statistical Signal Processing Workshop},\n  year={2023},\n}\n

\n\n\n\n

\n\n\n

\n \n\n \n \n \n \n \n \n Optimized preprocessing and Tiny ML for Attention State Classification.\n \n \n \n \n\n\n \n Wang, Y.; Nahon, R.; Tartaglione, E.; Mozharovskyi, P.; and Nguyen, V.\n\n\n \n\n\n\n In 22nd IEEE Statistical Signal Processing Workshop, 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Optimized$ 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

@inproceedings{wang2023optimized,\n  title={Optimized preprocessing and Tiny ML for Attention State Classification},\n  author={Wang, Yinghao and Nahon, R{\\&#x27;e}mi and Tartaglione, Enzo and Mozharovskyi, Pavlo and Nguyen, Van-Tam},\n  booktitle={22nd IEEE Statistical Signal Processing Workshop},\n  year={2023},\n  url={https://arxiv.org/pdf/2303.11371}\n}\n

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\n \n\n \n \n \n \n \n \n Unbiased Supervised Contrastive Learning.\n \n \n \n \n\n\n \n Barbano, C. A.; Dufumier, B.; Tartaglione, E.; Grangetto, M.; and Gori, P.\n\n\n \n\n\n\n In The Eleventh International Conference on Learning Representations , 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Unbiased$ Paper\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

@inproceedings{\nbarbano2023unbiased,\ntitle={Unbiased Supervised Contrastive Learning},\nauthor={Carlo Alberto Barbano and Benoit Dufumier and Enzo Tartaglione and Marco Grangetto and Pietro Gori},\nbooktitle={The Eleventh International Conference on Learning Representations },\nyear={2023},\nurl={https://openreview.net/forum?id=Ph5cJSfD2XN}\n}\n

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\n \n\n \n \n \n \n \n \n Packed Ensembles for efficient uncertainty estimation.\n \n \n \n \n\n\n \n Laurent, O.; Lafage, A.; Tartaglione, E.; Daniel, G.; Martinez, J.; Bursuc, A.; and Franchi, G.\n\n\n \n\n\n\n In The Eleventh International Conference on Learning Representations (spotlight paper), 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Packed$ 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

@inproceedings{laurent2023packed,\ntitle={Packed Ensembles for efficient uncertainty estimation},\nauthor={Olivier Laurent and Adrien Lafage and Enzo Tartaglione and Geoffrey Daniel and Jean-marc Martinez and Andrei Bursuc and Gianni Franchi},\nbooktitle={The Eleventh International Conference on Learning Representations (spotlight paper)},\nyear={2023},\nurl={https://openreview.net/forum?id=XXTyv1zD9zD}\n}\n

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\n \n\n \n \n \n \n \n \n Compressing Explicit Voxel Grid Representations: Fast NeRFs Become Also Small.\n \n \n \n \n\n\n \n Deng, C. L.; and Tartaglione, E.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pages 1236-1245, January 2023. \n \n\n\n\n
\n\n\n\n \n \n $\"Compressing$ Paper\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

@InProceedings{Deng_2023_WACV,\n    author    = {Deng, Chenxi Lola and Tartaglione, Enzo},\n    title     = {Compressing Explicit Voxel Grid Representations: Fast NeRFs Become Also Small},\n    booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},\n    month     = {January},\n    year      = {2023},\n    pages     = {1236-1245},\n    url={https://openaccess.thecvf.com/content/WACV2023/papers/Deng_Compressing_Explicit_Voxel_Grid_Representations_Fast_NeRFs_Become_Also_Small_WACV_2023_paper.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke.\n \n \n \n \n\n\n \n Gava, U. A.; D’Agata, F.; Tartaglione, E.; Renzulli, R.; Grangetto, M.; Bertolino, F.; Santonocito, A.; Bennink, E.; Vaudano, G.; Boghi, A.; and Bergui, M.\n\n\n \n\n\n\n Frontiers in Neuroinformatics, 17. 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Neural$ 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 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@ARTICLE{10.3389/fninf.2023.852105,\nAUTHOR={Gava, Umberto A. and D’Agata, Federico and Tartaglione, Enzo and Renzulli, Riccardo and Grangetto, Marco and Bertolino, Francesca and Santonocito, Ambra and Bennink, Edwin and Vaudano, Giacomo and Boghi, Andrea and Bergui, Mauro},\nTITLE={Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke},      \nJOURNAL={Frontiers in Neuroinformatics},\nVOLUME={17},           \nYEAR={2023},\nURL={https://www.frontiersin.org/articles/10.3389/fninf.2023.852105},       \nDOI={10.3389/fninf.2023.852105},\nISSN={1662-5196},   \n}\n

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\n \n 2022\n \n \n (9)\n \n \n

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\n \n\n \n \n \n \n \n \n The Rise of the Lottery Heroes: Why Zero-Shot Pruning is Hard.\n \n \n \n \n\n\n \n Tartaglione, E.\n\n\n \n\n\n\n In 2022 IEEE International Conference on Image Processing (ICIP), pages 2361-2365, 2022. \n \n\n\n\n
\n\n\n\n \n \n $\"The$ 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 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

@INPROCEEDINGS{9897223,\n  author={Tartaglione, Enzo},\n  booktitle={2022 IEEE International Conference on Image Processing (ICIP)}, \n  title={The Rise of the Lottery Heroes: Why Zero-Shot Pruning is Hard}, \n  year={2022},\n  volume={},\n  number={},\n  pages={2361-2365},\n  doi={10.1109/ICIP46576.2022.9897223},\n  url={https://hal.archives-ouvertes.fr/hal-03766740/document}\n  }\n

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\n \n\n \n \n \n \n \n \n To update or not to update? Neurons at equilibrium in deep models.\n \n \n \n \n\n\n \n Bragagnolo, A.; Tartaglione, E.; and Grangetto, M.\n\n\n \n\n\n\n Advances in Neural Information Processing Systems, 35: 22149–22160. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"To$ 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

@article{bragagnolo2022update,\n  title={To update or not to update? Neurons at equilibrium in deep models},\n  author={Bragagnolo, Andrea and Tartaglione, Enzo and Grangetto, Marco},\n  journal={Advances in Neural Information Processing Systems},\n  volume={35},\n  pages={22149--22160},\n  year={2022},\n  url={https://proceedings.neurips.cc/paper_files/paper/2022/file/8b2fc235787852ead92da2268cd9e90c-Paper-Conference.pdf},\n}\n

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\n \n\n \n \n \n \n \n \n Information Removal at the bottleneck in Deep Neural Networks.\n \n \n \n \n\n\n \n Tartaglione, E.\n\n\n \n\n\n\n In 33rd British Machine Vision Conference 2022, BMVC 2022, London, UK, November 21-24, 2022, 2022. BMVA Press\n \n\n\n\n
\n\n\n\n \n \n $\"Information$ 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

@inproceedings{Tartaglione_2022_BMVC,\nauthor    = {Enzo Tartaglione},\ntitle     = {Information Removal at the bottleneck in Deep Neural Networks},\nbooktitle = {33rd British Machine Vision Conference 2022, {BMVC} 2022, London, UK, November 21-24, 2022},\npublisher = {{BMVA} Press},\nyear      = {2022},\nurl       = {https://bmvc2022.mpi-inf.mpg.de/0488.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Loss-based sensitivity regularization: towards deep sparse neural networks.\n \n \n \n \n\n\n \n Tartaglione, E.; Bragagnolo, A.; Fiandrotti, A.; and Grangetto, M.\n\n\n \n\n\n\n Neural Networks, 146: 230–237. 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Loss-based$ Paper\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

@article{tartaglione2022loss,\n  title={Loss-based sensitivity regularization: towards deep sparse neural networks},\n  author={Tartaglione, Enzo and Bragagnolo, Andrea and Fiandrotti, Attilio and Grangetto, Marco},\n  journal={Neural Networks},\n  volume={146},\n  pages={230--237},\n  year={2022},\n  publisher={Elsevier},\n  url={https://arxiv.org/pdf/2011.09905}\n}\n

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\n \n\n \n \n \n \n \n Applications of AI and HPC in the Health Domain.\n \n \n \n\n\n \n Oniga, D.; Cantalupo, B.; Tartaglione, E.; Perlo, D.; Grangetto, M.; Aldinucci, M.; Bolelli, F.; Pollastri, F.; Cancilla, M.; Canalini, L.; and others\n\n\n \n\n\n\n In HPC, Big Data, and AI Convergence Towards Exascale, pages 217–239. CRC Press, 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

@incollection{oniga2022applications,\n  title={Applications of AI and HPC in the Health Domain},\n  author={Oniga, Dana and Cantalupo, Barbara and Tartaglione, Enzo and Perlo, Daniele and Grangetto, Marco and Aldinucci, Marco and Bolelli, Federico and Pollastri, Federico and Cancilla, Michele and Canalini, Laura and others},\n  booktitle={HPC, Big Data, and AI Convergence Towards Exascale},\n  pages={217--239},\n  year={2022},\n  publisher={CRC Press}\n}\n

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\n \n\n \n \n \n \n \n The DeepHealth HPC Infrastructure: Leveraging Heterogenous HPC and Cloud-Computing Infrastructures for IA-Based Medical Solutions.\n \n \n \n\n\n \n Quiñones, E.; Perales, J.; Ejarque, J.; Badouh, A.; Marco, S.; Auzanneau, F.; Galea, F.; Gonz'alez, D.; Herv'as, J. R.; Silva, T.; and others\n\n\n \n\n\n\n In HPC, Big Data, and AI Convergence Towards Exascale, pages 191–216. CRC Press, 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

@incollection{quinones2022deephealth,\n  title={The DeepHealth HPC Infrastructure: Leveraging Heterogenous HPC and Cloud-Computing Infrastructures for IA-Based Medical Solutions},\n  author={Qui{\\~n}ones, Eduardo and Perales, Jesus and Ejarque, Jorge and Badouh, Asaf and Marco, Santiago and Auzanneau, Fabrice and Galea, Fran{\\c{c}}ois and Gonz{\\&#x27;a}lez, David and Herv{\\&#x27;a}s, Jos{\\&#x27;e} Ram{\\&#x27;o}n and Silva, Tatiana and others},\n  booktitle={HPC, Big Data, and AI Convergence Towards Exascale},\n  pages={191--216},\n  year={2022},\n  publisher={CRC Press}\n}\n

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\n \n\n \n \n \n \n \n \n A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images.\n \n \n \n \n\n\n \n Barbano, C. A.; Tartaglione, E.; Berzovini, C.; Calandri, M.; and Grangetto, M.\n\n\n \n\n\n\n In International Conference on Image Analysis and Processing, pages 173–184, 2022. Springer\n \n\n\n\n
\n\n\n\n \n \n $\"A$ 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

@inproceedings{barbano2022two,\n  title={A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images},\n  author={Barbano, Carlo Alberto and Tartaglione, Enzo and Berzovini, Claudio and Calandri, Marco and Grangetto, Marco},\n  booktitle={International Conference on Image Analysis and Processing},\n  pages={173--184},\n  year={2022},\n  organization={Springer},\n  url={https://link.springer.com/chapter/10.1007/978-3-031-06427-2_15}\n}\n

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\n \n\n \n \n \n \n \n Marco Aldinucci, David Atienza, Federico Bolelli, M'onica Caballero, Iacopo Colonnelli, Jos'e Flich, Jon A. G'omez, David Gonz'alez, Costantino Grana, Marco Grangetto, Simone Leo, Pedro L'opez, Dana Oniga, Roberto Paredes, Luca Pireddu, Eduardo Quiñones, Tatiana Silva.\n \n \n \n\n\n \n Tartaglione, E.; and Zapater, M.\n\n\n \n\n\n\n Technologies and Applications for Big Data Value,183. 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

@article{tartaglione2022marco,\n  title={Marco Aldinucci, David Atienza, Federico Bolelli, M{\\&#x27;o}nica Caballero, Iacopo Colonnelli, Jos{\\&#x27;e} Flich, Jon A. G{\\&#x27;o}mez, David Gonz{\\&#x27;a}lez, Costantino Grana, Marco Grangetto, Simone Leo, Pedro L{\\&#x27;o}pez, Dana Oniga, Roberto Paredes, Luca Pireddu, Eduardo Qui{\\~n}ones, Tatiana Silva},\n  author={Tartaglione, Enzo and Zapater, Marina},\n  journal={Technologies and Applications for Big Data Value},\n  pages={183},\n  year={2022},\n  publisher={Springer Nature}\n}\n

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\n \n\n \n \n \n \n \n The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures.\n \n \n \n\n\n \n Aldinucci, M.; Atienza, D.; Bolelli, F.; Caballero, M.; Colonnelli, I.; Flich, J.; G'omez, J. A; Gonz'alez, D.; Grana, C.; Grangetto, M.; and others\n\n\n \n\n\n\n In Technologies and Applications for Big Data Value, pages 183–202. Springer, 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

@incollection{aldinucci2022deephealth,\n  title={The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures},\n  author={Aldinucci, Marco and Atienza, David and Bolelli, Federico and Caballero, M{\\&#x27;o}nica and Colonnelli, Iacopo and Flich, Jos{\\&#x27;e} and G{\\&#x27;o}mez, Jon A and Gonz{\\&#x27;a}lez, David and Grana, Costantino and Grangetto, Marco and others},\n  booktitle={Technologies and Applications for Big Data Value},\n  pages={183--202},\n  year={2022},\n  publisher={Springer}\n}\n

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\n \n 2021\n \n \n (10)\n \n \n

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\n \n\n \n \n \n \n \n \n End: Entangling and disentangling deep representations for bias correction.\n \n \n \n \n\n\n \n Tartaglione, E.; Barbano, C. A.; and Grangetto, M.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 13508–13517, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"End:$ Paper\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

@inproceedings{tartaglione2021end,\n  title={End: Entangling and disentangling deep representations for bias correction},\n  author={Tartaglione, Enzo and Barbano, Carlo Alberto and Grangetto, Marco},\n  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},\n  pages={13508--13517},\n  year={2021},\n  url={https://openaccess.thecvf.com/content/CVPR2021/papers/Tartaglione_EnD_Entangling_and_Disentangling_Deep_Representations_for_Bias_Correction_CVPR_2021_paper.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Serene: Sensitivity-based regularization of neurons for structured sparsity in neural networks.\n \n \n \n \n\n\n \n Tartaglione, E.; Bragagnolo, A.; Odierna, F.; Fiandrotti, A.; and Grangetto, M.\n\n\n \n\n\n\n IEEE Transactions on Neural Networks and Learning Systems. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Serene:$ 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

@article{tartaglione2021serene,\n  title={Serene: Sensitivity-based regularization of neurons for structured sparsity in neural networks},\n  author={Tartaglione, Enzo and Bragagnolo, Andrea and Odierna, Francesco and Fiandrotti, Attilio and Grangetto, Marco},\n  journal={IEEE Transactions on Neural Networks and Learning Systems},\n  year={2021},\n  publisher={IEEE},\n  url={https://arxiv.org/pdf/2102.03773}\n}\n

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\n \n\n \n \n \n \n \n \n HEMP: High-order entropy minimization for neural network compression.\n \n \n \n \n\n\n \n Tartaglione, E.; Lathuili`ere, S.; Fiandrotti, A.; Cagnazzo, M.; and Grangetto, M.\n\n\n \n\n\n\n Neurocomputing, 461: 244–253. 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"HEMP:$ Paper\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

@article{tartaglione2021hemp,\n  title={HEMP: High-order entropy minimization for neural network compression},\n  author={Tartaglione, Enzo and Lathuili{\\&#x60;e}re, St{\\&#x27;e}phane and Fiandrotti, Attilio and Cagnazzo, Marco and Grangetto, Marco},\n  journal={Neurocomputing},\n  volume={461},\n  pages={244--253},\n  year={2021},\n  publisher={Elsevier},\n  url={https://www.sciencedirect.com/science/article/pii/S0925231221010663}\n}\n

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\n \n\n \n \n \n \n \n \n UniToPatho, a labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading.\n \n \n \n \n\n\n \n Barbano, C. A.; Perlo, D.; Tartaglione, E.; Fiandrotti, A.; Bertero, L.; Cassoni, P.; and Grangetto, M.\n\n\n \n\n\n\n In 2021 IEEE International Conference on Image Processing (ICIP), pages 76–80, 2021. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"UniToPatho,$ 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

@inproceedings{barbano2021unitopatho,\n  title={UniToPatho, a labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading},\n  author={Barbano, Carlo Alberto and Perlo, Daniele and Tartaglione, Enzo and Fiandrotti, Attilio and Bertero, Luca and Cassoni, Paola and Grangetto, Marco},\n  booktitle={2021 IEEE International Conference on Image Processing (ICIP)},\n  pages={76--80},\n  year={2021},\n  organization={IEEE},\n  url={https://ieeexplore.ieee.org/document/9506198}\n}\n

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\n \n\n \n \n \n \n \n \n Delving in the loss landscape to embed robust watermarks into neural networks.\n \n \n \n \n\n\n \n Tartaglione, E.; Grangetto, M.; Cavagnino, D.; and Botta, M.\n\n\n \n\n\n\n In 2020 25th International Conference on Pattern Recognition (ICPR), pages 1243–1250, 2021. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Delving$ 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

@inproceedings{tartaglione2021delving,\n  title={Delving in the loss landscape to embed robust watermarks into neural networks},\n  author={Tartaglione, Enzo and Grangetto, Marco and Cavagnino, Davide and Botta, Marco},\n  booktitle={2020 25th International Conference on Pattern Recognition (ICPR)},\n  pages={1243--1250},\n  year={2021},\n  organization={IEEE},\n  url={https://ieeexplore.ieee.org/document/9413062}\n}\n

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\n \n\n \n \n \n \n \n \n On the role of structured pruning for neural network compression.\n \n \n \n \n\n\n \n Bragagnolo, A.; Tartaglione, E.; Fiandrotti, A.; and Grangetto, M.\n\n\n \n\n\n\n In 2021 IEEE International Conference on Image Processing (ICIP), pages 3527–3531, 2021. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"On$ 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

@inproceedings{bragagnolo2021role,\n  title={On the role of structured pruning for neural network compression},\n  author={Bragagnolo, Andrea and Tartaglione, Enzo and Fiandrotti, Attilio and Grangetto, Marco},\n  booktitle={2021 IEEE International Conference on Image Processing (ICIP)},\n  pages={3527--3531},\n  year={2021},\n  organization={IEEE},\n  url={https://iris.unito.it/retrieve/e27ce432-d3d0-2581-e053-d805fe0acbaa/ICIP2021_pruning.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Bridging the gap between debiasing and privacy for deep learning.\n \n \n \n \n\n\n \n Barbano, C. A.; Tartaglione, E.; and Grangetto, M.\n\n\n \n\n\n\n In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 3806–3815, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"Bridging$ 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

@inproceedings{barbano2021bridging,\n  title={Bridging the gap between debiasing and privacy for deep learning},\n  author={Barbano, Carlo Alberto and Tartaglione, Enzo and Grangetto, Marco},\n  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},\n  pages={3806--3815},\n  year={2021},\n  url={https://openaccess.thecvf.com/content/ICCV2021W/RPRMI/papers/Barbano_Bridging_the_Gap_Between_Debiasing_and_Privacy_for_Deep_Learning_ICCVW_2021_paper.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Capsule Networks with Routing Annealing.\n \n \n \n \n\n\n \n Renzulli, R.; Tartaglione, E.; Fiandrotti, A.; and Grangetto, M.\n\n\n \n\n\n\n In International Conference on Artificial Neural Networks, pages 529–540, 2021. Springer\n \n\n\n\n
\n\n\n\n \n \n $\"Capsule$ 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

@inproceedings{renzulli2021capsule,\n  title={Capsule Networks with Routing Annealing},\n  author={Renzulli, Riccardo and Tartaglione, Enzo and Fiandrotti, Attilio and Grangetto, Marco},\n  booktitle={International Conference on Artificial Neural Networks},\n  pages={529--540},\n  year={2021},\n  organization={Springer},\n  url={https://iris.unito.it/retrieve/e27ce434-ea60-2581-e053-d805fe0acbaa/ICANN21_capsule.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n A Hitchhiker’s Guide towards Transactive Memory System Modeling in Small Group Interactions.\n \n \n \n \n\n\n \n Tartaglione, E.; Biancardi, B.; Mancini, M.; and Varni, G.\n\n\n \n\n\n\n In Companion Publication of the 2021 International Conference on Multimodal Interaction, pages 254–262, 2021. \n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\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

@inproceedings{tartaglione2021hitchhiker,\n  title={A Hitchhiker’s Guide towards Transactive Memory System Modeling in Small Group Interactions},\n  author={Tartaglione, Enzo and Biancardi, Beatrice and Mancini, Maurizio and Varni, Giovanna},\n  booktitle={Companion Publication of the 2021 International Conference on Multimodal Interaction},\n  pages={254--262},\n  year={2021},\n  url={https://dl.acm.org/doi/10.1145/3461615.3485414}\n}\n

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\n \n\n \n \n \n \n \n \n Dysplasia grading of colorectal polyps through convolutional neural network analysis of whole slide images.\n \n \n \n \n\n\n \n Perlo, D.; Tartaglione, E.; Bertero, L.; Cassoni, P.; and Grangetto, M.\n\n\n \n\n\n\n In International Conference on Medical Imaging and Computer-Aided Diagnosis, pages 325–334, 2021. Springer\n \n\n\n\n
\n\n\n\n \n \n $\"Dysplasia$ 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

@inproceedings{perlo2021dysplasia,\n  title={Dysplasia grading of colorectal polyps through convolutional neural network analysis of whole slide images},\n  author={Perlo, Daniele and Tartaglione, Enzo and Bertero, Luca and Cassoni, Paola and Grangetto, Marco},\n  booktitle={International Conference on Medical Imaging and Computer-Aided Diagnosis},\n  pages={325--334},\n  year={2021},\n  organization={Springer},\n  url={https://link.springer.com/chapter/10.1007/978-981-16-3880-0_34}\n}\n

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\n \n 2020\n \n \n (3)\n \n \n

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\n \n\n \n \n \n \n \n \n Unveiling covid-19 from chest x-ray with deep learning: a hurdles race with small data.\n \n \n \n \n\n\n \n Tartaglione, E.; Barbano, C. A.; Berzovini, C.; Calandri, M.; and Grangetto, M.\n\n\n \n\n\n\n International Journal of Environmental Research and Public Health, 17(18): 6933. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Unveiling$ 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

@article{tartaglione2020unveiling,\n  title={Unveiling covid-19 from chest x-ray with deep learning: a hurdles race with small data},\n  author={Tartaglione, Enzo and Barbano, Carlo Alberto and Berzovini, Claudio and Calandri, Marco and Grangetto, Marco},\n  journal={International Journal of Environmental Research and Public Health},\n  volume={17},\n  number={18},\n  pages={6933},\n  year={2020},\n  publisher={MDPI},\n  url={https://www.mdpi.com/1660-4601/17/18/6933}\n}\n

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\n \n\n \n \n \n \n \n \n Pruning artificial neural networks: A way to find well-generalizing, high-entropy sharp minima.\n \n \n \n \n\n\n \n Tartaglione, E.; Bragagnolo, A.; and Grangetto, M.\n\n\n \n\n\n\n In International Conference on Artificial Neural Networks, pages 67–78, 2020. Springer\n \n\n\n\n
\n\n\n\n \n \n $\"Pruning$ 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

@inproceedings{tartaglione2020pruning,\n  title={Pruning artificial neural networks: A way to find well-generalizing, high-entropy sharp minima},\n  author={Tartaglione, Enzo and Bragagnolo, Andrea and Grangetto, Marco},\n  booktitle={International Conference on Artificial Neural Networks},\n  pages={67--78},\n  year={2020},\n  organization={Springer},\n  url={https://arxiv.org/pdf/2004.14765}\n}\n

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\n \n\n \n \n \n \n \n \n A non-discriminatory approach to ethical deep learning.\n \n \n \n \n\n\n \n Tartaglione, E.; and Grangetto, M.\n\n\n \n\n\n\n In 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pages 943–950, 2020. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"A$ 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

@inproceedings{tartaglione2020non,\n  title={A non-discriminatory approach to ethical deep learning},\n  author={Tartaglione, Enzo and Grangetto, Marco},\n  booktitle={2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)},\n  pages={943--950},\n  year={2020},\n  organization={IEEE},\n  url={https://arxiv.org/pdf/2008.01430}\n}\n

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\n \n 2019\n \n \n (2)\n \n \n

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\n \n\n \n \n \n \n \n \n Take a ramble into solution spaces for classification problems in neural networks.\n \n \n \n \n\n\n \n Tartaglione, E.; and Grangetto, M.\n\n\n \n\n\n\n In International conference on image analysis and processing, pages 345–355, 2019. Springer\n \n\n\n\n
\n\n\n\n \n \n $\"Take$ 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

@inproceedings{tartaglione2019take,\n  title={Take a ramble into solution spaces for classification problems in neural networks},\n  author={Tartaglione, Enzo and Grangetto, Marco},\n  booktitle={International conference on image analysis and processing},\n  pages={345--355},\n  year={2019},\n  organization={Springer},\n  url={https://iris.unito.it/retrieve/e27ce42e-7422-2581-e053-d805fe0acbaa/ICIAP19_takearamble.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Post-synaptic potential regularization has potential.\n \n \n \n \n\n\n \n Tartaglione, E.; Perlo, D.; and Grangetto, M.\n\n\n \n\n\n\n In International Conference on Artificial Neural Networks, pages 187–200, 2019. Springer\n \n\n\n\n
\n\n\n\n \n \n $\"Post-synaptic$ 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

@inproceedings{tartaglione2019post,\n  title={Post-synaptic potential regularization has potential},\n  author={Tartaglione, Enzo and Perlo, Daniele and Grangetto, Marco},\n  booktitle={International Conference on Artificial Neural Networks},\n  pages={187--200},\n  year={2019},\n  organization={Springer},\n  url={https://arxiv.org/pdf/1907.08544}\n}\n

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\n \n 2018\n \n \n (2)\n \n \n

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\n \n\n \n \n \n \n \n \n Learning sparse neural networks via sensitivity-driven regularization.\n \n \n \n \n\n\n \n Tartaglione, E.; Lepsøy, S.; Fiandrotti, A.; and Francini, G.\n\n\n \n\n\n\n Advances in neural information processing systems, 31. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Learning$ 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

@article{tartaglione2018learning,\n  title={Learning sparse neural networks via sensitivity-driven regularization},\n  author={Tartaglione, Enzo and Leps{\\o}y, Skjalg and Fiandrotti, Attilio and Francini, Gianluca},\n  journal={Advances in neural information processing systems},\n  volume={31},\n  year={2018},\n  url={https://proceedings.neurips.cc/paper/2018/file/04df4d434d481c5bb723be1b6df1ee65-Paper.pdf}\n}\n

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\n \n\n \n \n \n \n \n \n Role of synaptic stochasticity in training low-precision neural networks.\n \n \n \n \n\n\n \n Baldassi, C.; Gerace, F.; Kappen, H. J; Lucibello, C.; Saglietti, L.; Tartaglione, E.; and Zecchina, R.\n\n\n \n\n\n\n Physical review letters, 120(26): 268103. 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Role$ 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

@article{baldassi2018role,\n  title={Role of synaptic stochasticity in training low-precision neural networks},\n  author={Baldassi, Carlo and Gerace, Federica and Kappen, Hilbert J and Lucibello, Carlo and Saglietti, Luca and Tartaglione, Enzo and Zecchina, Riccardo},\n  journal={Physical review letters},\n  volume={120},\n  number={26},\n  pages={268103},\n  year={2018},\n  publisher={APS},\n  url={https://arxiv.org/pdf/1710.09825}\n}\n

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\n \n 2015\n \n \n (1)\n \n \n

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\n \n\n \n \n \n \n \n \n Communication scheduling and buslet synthesis for low-interconnect HLS designs.\n \n \n \n \n\n\n \n Tartaglione, E.; and Dutt, S.\n\n\n \n\n\n\n In 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), pages 86–93, 2015. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Communication$ 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

@inproceedings{tartaglione2015communication,\n  title={Communication scheduling and buslet synthesis for low-interconnect HLS designs},\n  author={Tartaglione, Enzo and Dutt, Shantanu},\n  booktitle={2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)},\n  pages={86--93},\n  year={2015},\n  organization={IEEE},\n  url={https://ieeexplore.ieee.org/abstract/document/7372554}\n}

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