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\n\n \n \n \n \n \n \n Memory-aware and context-aware multi-DNN inference on the edge.\n \n \n \n \n\n\n \n Cox, B.; Birke, R.; and Chen, L. Y.\n\n\n \n\n\n\n
Pervasive Mob. Comput., 83: 101594. 2022.\n
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@article{DBLP:journals/percom/CoxBC22,\n author = {Bart Cox and\n Robert Birke and\n Lydia Y. Chen},\n title = {Memory-aware and context-aware multi-DNN inference on the edge},\n journal = {Pervasive Mob. Comput.},\n volume = {83},\n pages = {101594},\n year = {2022},\n url = {https://doi.org/10.1016/j.pmcj.2022.101594},\n doi = {10.1016/J.PMCJ.2022.101594},\n timestamp = {Wed, 27 Jul 2022 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/percom/CoxBC22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G.\n \n \n \n \n\n\n \n Wang, J.; Han, H.; Li, H.; He, S.; Sharma, P. K.; and Chen, L. Y.\n\n\n \n\n\n\n
IEEE Trans. Ind. Informatics, 18(3): 1939–1948. 2022.\n
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@article{DBLP:journals/tii/WangHLHSC22,\n author = {Jin Wang and\n Hui Han and\n Hao Li and\n Shiming He and\n Pradip Kumar Sharma and\n Lydia Y. Chen},\n title = {Multiple Strategies Differential Privacy on Sparse Tensor Factorization\n for Network Traffic Analysis in 5G},\n journal = {{IEEE} Trans. Ind. Informatics},\n volume = {18},\n number = {3},\n pages = {1939--1948},\n year = {2022},\n url = {https://doi.org/10.1109/TII.2021.3082576},\n doi = {10.1109/TII.2021.3082576},\n timestamp = {Mon, 28 Aug 2023 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/tii/WangHLHSC22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Lightweight and Accurate DNN-Based Anomaly Detection at Edge.\n \n \n \n \n\n\n \n Zhang, Q.; Han, R.; Xin, G.; Liu, C. H.; Wang, G.; and Chen, L. Y.\n\n\n \n\n\n\n
IEEE Trans. Parallel Distributed Syst., 33(11): 2927–2942. 2022.\n
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@article{DBLP:journals/tpds/ZhangHXLWC22,\n author = {Qinglong Zhang and\n Rui Han and\n Gaofeng Xin and\n Chi Harold Liu and\n Guoren Wang and\n Lydia Y. Chen},\n title = {Lightweight and Accurate DNN-Based Anomaly Detection at Edge},\n journal = {{IEEE} Trans. Parallel Distributed Syst.},\n volume = {33},\n number = {11},\n pages = {2927--2942},\n year = {2022},\n url = {https://doi.org/10.1109/TPDS.2021.3137631},\n doi = {10.1109/TPDS.2021.3137631},\n timestamp = {Mon, 13 Jun 2022 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/tpds/ZhangHXLWC22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Federated Learning With Heterogeneity-Aware Probabilistic Synchronous Parallel on Edge.\n \n \n \n \n\n\n \n Zhao, J.; Han, R.; Yang, Y.; Catterall, B.; Liu, C. H.; Chen, L. Y.; Mortier, R.; Crowcroft, J.; and Wang, L.\n\n\n \n\n\n\n
IEEE Trans. Serv. Comput., 15(2): 614–626. 2022.\n
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@article{DBLP:journals/tsc/ZhaoHYCLCMCW22,\n author = {Jianxin Zhao and\n Rui Han and\n Yongkai Yang and\n Benjamin Catterall and\n Chi Harold Liu and\n Lydia Y. Chen and\n Richard Mortier and\n Jon Crowcroft and\n Liang Wang},\n title = {Federated Learning With Heterogeneity-Aware Probabilistic Synchronous\n Parallel on Edge},\n journal = {{IEEE} Trans. Serv. Comput.},\n volume = {15},\n number = {2},\n pages = {614--626},\n year = {2022},\n url = {https://doi.org/10.1109/TSC.2021.3109910},\n doi = {10.1109/TSC.2021.3109910},\n timestamp = {Fri, 05 May 2023 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/tsc/ZhaoHYCLCMCW22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Trusted Loss Correction for Noisy Multi-Label Learning.\n \n \n \n \n\n\n \n Ghiassi, A.; Pene, C. O.; Birke, R.; and Chen, L. Y.\n\n\n \n\n\n\n In Balasubramanian, V. N.; and Tsang, I. W., editor(s),
Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India, volume 189, of
Proceedings of Machine Learning Research, pages 343–358, 2022. PMLR\n
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@inproceedings{DBLP:conf/acml/GhiassiPBC22,\n author = {Amirmasoud Ghiassi and\n Cosmin Octavian Pene and\n Robert Birke and\n Lydia Y. Chen},\n editor = {Vineeth N. Balasubramanian and\n Ivor W. Tsang},\n title = {Trusted Loss Correction for Noisy Multi-Label Learning},\n booktitle = {Asian Conference on Machine Learning, {ACML} 2022, 12-14 December\n 2022, Hyderabad, India},\n series = {Proceedings of Machine Learning Research},\n volume = {189},\n pages = {343--358},\n publisher = {{PMLR}},\n year = {2022},\n url = {https://proceedings.mlr.press/v189/ghiassi23a.html},\n timestamp = {Tue, 07 May 2024 20:11:56 +0200},\n biburl = {https://dblp.org/rec/conf/acml/GhiassiPBC22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Multi Label Loss Correction against Missing and Corrupted Labels.\n \n \n \n \n\n\n \n Ghiassi, A.; Birke, R.; and Chen, L. Y.\n\n\n \n\n\n\n In Balasubramanian, V. N.; and Tsang, I. W., editor(s),
Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India, volume 189, of
Proceedings of Machine Learning Research, pages 359–374, 2022. PMLR\n
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@inproceedings{DBLP:conf/acml/GhiassiBC22,\n author = {Amirmasoud Ghiassi and\n Robert Birke and\n Lydia Y. Chen},\n editor = {Vineeth N. Balasubramanian and\n Ivor W. Tsang},\n title = {Multi Label Loss Correction against Missing and Corrupted Labels},\n booktitle = {Asian Conference on Machine Learning, {ACML} 2022, 12-14 December\n 2022, Hyderabad, India},\n series = {Proceedings of Machine Learning Research},\n volume = {189},\n pages = {359--374},\n publisher = {{PMLR}},\n year = {2022},\n url = {https://proceedings.mlr.press/v189/ghiassi23b.html},\n timestamp = {Tue, 20 Jun 2023 01:00:00 +0200},\n biburl = {https://dblp.org/rec/conf/acml/GhiassiBC22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Permutation-Invariant Tabular Data Synthesis.\n \n \n \n \n\n\n \n Zhu, Y.; Zhao, Z.; Birke, R.; and Chen, L. Y.\n\n\n \n\n\n\n In Tsumoto, S.; Ohsawa, Y.;
Chen, L.; den Poel, D. V.; Hu, X.; Motomura, Y.; Takagi, T.; Wu, L.; Xie, Y.; Abe, A.; and Raghavan, V., editor(s),
IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan, December 17-20, 2022, pages 5855–5864, 2022. IEEE\n
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@inproceedings{DBLP:conf/bigdataconf/ZhuZBC22,\n author = {Yujin Zhu and\n Zilong Zhao and\n Robert Birke and\n Lydia Y. Chen},\n editor = {Shusaku Tsumoto and\n Yukio Ohsawa and\n Lei Chen and\n Dirk Van den Poel and\n Xiaohua Hu and\n Yoichi Motomura and\n Takuya Takagi and\n Lingfei Wu and\n Ying Xie and\n Akihiro Abe and\n Vijay Raghavan},\n title = {Permutation-Invariant Tabular Data Synthesis},\n booktitle = {{IEEE} International Conference on Big Data, Big Data 2022, Osaka,\n Japan, December 17-20, 2022},\n pages = {5855--5864},\n publisher = {{IEEE}},\n year = {2022},\n url = {https://doi.org/10.1109/BigData55660.2022.10020639},\n doi = {10.1109/BIGDATA55660.2022.10020639},\n timestamp = {Tue, 11 Jun 2024 10:44:02 +0200},\n biburl = {https://dblp.org/rec/conf/bigdataconf/ZhuZBC22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Targeted Influence with Community and Gender-Aware Seeding.\n \n \n \n \n\n\n \n Styczen, M.; Chen, B.; Teng, Y.; Pignolet, Y.; Chen, L. Y.; and Yang, D.\n\n\n \n\n\n\n In Hasan, M. A.; and Xiong, L., editor(s),
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, October 17-21, 2022, pages 4515–4519, 2022. ACM\n
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@inproceedings{DBLP:conf/cikm/StyczenCTPCY22,\n author = {Maciej Styczen and\n Bing{-}Jyue Chen and\n Ya{-}Wen Teng and\n Yvonne{-}Anne Pignolet and\n Lydia Y. Chen and\n De{-}Nian Yang},\n editor = {Mohammad Al Hasan and\n Li Xiong},\n title = {Targeted Influence with Community and Gender-Aware Seeding},\n booktitle = {Proceedings of the 31st {ACM} International Conference on Information\n {\\&} Knowledge Management, Atlanta, GA, USA, October 17-21, 2022},\n pages = {4515--4519},\n publisher = {{ACM}},\n year = {2022},\n url = {https://doi.org/10.1145/3511808.3557708},\n doi = {10.1145/3511808.3557708},\n timestamp = {Wed, 19 Oct 2022 12:52:00 +0200},\n biburl = {https://dblp.org/rec/conf/cikm/StyczenCTPCY22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n LABNET: A Collaborative Method for DNN Training and Label Aggregation.\n \n \n \n \n\n\n \n Ghiassi, A.; Birke, R.; and Chen, L. Y.\n\n\n \n\n\n\n In Rocha, A. P.; Steels, L.; and van den Herik, H. J., editor(s),
Proceedings of the 14th International Conference on Agents and Artificial Intelligence, ICAART 2022, Volume 2, Online Streaming, February 3-5, 2022, pages 56–66, 2022. SCITEPRESS\n
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@inproceedings{DBLP:conf/icaart/GhiassiBC22,\n author = {Amirmasoud Ghiassi and\n Robert Birke and\n Lydia Y. Chen},\n editor = {Ana Paula Rocha and\n Luc Steels and\n H. Jaap van den Herik},\n title = {{LABNET:} {A} Collaborative Method for {DNN} Training and Label Aggregation},\n booktitle = {Proceedings of the 14th International Conference on Agents and Artificial\n Intelligence, {ICAART} 2022, Volume 2, Online Streaming, February\n 3-5, 2022},\n pages = {56--66},\n publisher = {{SCITEPRESS}},\n year = {2022},\n url = {https://doi.org/10.5220/0010770400003116},\n doi = {10.5220/0010770400003116},\n timestamp = {Tue, 06 Jun 2023 14:58:00 +0200},\n biburl = {https://dblp.org/rec/conf/icaart/GhiassiBC22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n EdgeTuner: Fast Scheduling Algorithm Tuning for Dynamic Edge-Cloud Workloads and Resources.\n \n \n \n \n\n\n \n Han, R.; Wen, S.; Liu, C. H.; Yuan, Y.; Wang, G.; and Chen, L. Y.\n\n\n \n\n\n\n In
IEEE INFOCOM 2022 - IEEE Conference on Computer Communications, London, United Kingdom, May 2-5, 2022, pages 880–889, 2022. IEEE\n
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@inproceedings{DBLP:conf/infocom/HanWLYWC22,\n author = {Rui Han and\n Shilin Wen and\n Chi Harold Liu and\n Ye Yuan and\n Guoren Wang and\n Lydia Y. Chen},\n title = {EdgeTuner: Fast Scheduling Algorithm Tuning for Dynamic Edge-Cloud\n Workloads and Resources},\n booktitle = {{IEEE} {INFOCOM} 2022 - {IEEE} Conference on Computer Communications,\n London, United Kingdom, May 2-5, 2022},\n pages = {880--889},\n publisher = {{IEEE}},\n year = {2022},\n url = {https://doi.org/10.1109/INFOCOM48880.2022.9796792},\n doi = {10.1109/INFOCOM48880.2022.9796792},\n timestamp = {Tue, 28 Jun 2022 08:49:13 +0200},\n biburl = {https://dblp.org/rec/conf/infocom/HanWLYWC22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Federated Learning for Tabular Data: Exploring Potential Risk to Privacy.\n \n \n \n \n\n\n \n Wu, H.; Zhao, Z.; Chen, L. Y.; and van Moorsel, A.\n\n\n \n\n\n\n In
IEEE 33rd International Symposium on Software Reliability Engineering, ISSRE 2022, Charlotte, NC, USA, October 31 - Nov. 3, 2022, pages 193–204, 2022. IEEE\n
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@inproceedings{DBLP:conf/issre/Wu0CM22,\n author = {Han Wu and\n Zilong Zhao and\n Lydia Y. Chen and\n Aad van Moorsel},\n title = {Federated Learning for Tabular Data: Exploring Potential Risk to Privacy},\n booktitle = {{IEEE} 33rd International Symposium on Software Reliability Engineering,\n {ISSRE} 2022, Charlotte, NC, USA, October 31 - Nov. 3, 2022},\n pages = {193--204},\n publisher = {{IEEE}},\n year = {2022},\n url = {https://doi.org/10.1109/ISSRE55969.2022.00028},\n doi = {10.1109/ISSRE55969.2022.00028},\n timestamp = {Fri, 02 Aug 2024 01:00:00 +0200},\n biburl = {https://dblp.org/rec/conf/issre/Wu0CM22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n EdgeTune: Inference-Aware Multi-Parameter Tuning.\n \n \n \n \n\n\n \n Rocha, I.; Felber, P.; Schiavoni, V.; and Chen, L. Y.\n\n\n \n\n\n\n In Bellavista, P.; Zhang, K.; Gherbi, A.; Bagchi, S.; Patiño, M.; Modica, G. D.; and Gascon-Samson, J., editor(s),
Middleware '22: 23rd International Middleware Conference, Quebec, QC, Canada, November 7 - 11, 2022, pages 1–14, 2022. ACM\n
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@inproceedings{DBLP:conf/middleware/RochaFSC22,\n author = {Isabelly Rocha and\n Pascal Felber and\n Valerio Schiavoni and\n Lydia Y. Chen},\n editor = {Paolo Bellavista and\n Kaiwen Zhang and\n Abdelouahed Gherbi and\n Saurabh Bagchi and\n Marta Pati{\\~{n}}o and\n Giuseppe Di Modica and\n Julien Gascon{-}Samson},\n title = {EdgeTune: Inference-Aware Multi-Parameter Tuning},\n booktitle = {Middleware '22: 23rd International Middleware Conference, Quebec,\n QC, Canada, November 7 - 11, 2022},\n pages = {1--14},\n publisher = {{ACM}},\n year = {2022},\n url = {https://doi.org/10.1145/3528535.3533273},\n doi = {10.1145/3528535.3533273},\n timestamp = {Sun, 19 Jan 2025 00:00:00 +0100},\n biburl = {https://dblp.org/rec/conf/middleware/RochaFSC22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Aergia: leveraging heterogeneity in federated learning systems.\n \n \n \n \n\n\n \n Cox, B.; Chen, L. Y.; and Decouchant, J.\n\n\n \n\n\n\n In Bellavista, P.; Zhang, K.; Gherbi, A.; Bagchi, S.; Patiño, M.; Modica, G. D.; and Gascon-Samson, J., editor(s),
Middleware '22: 23rd International Middleware Conference, Quebec, QC, Canada, November 7 - 11, 2022, pages 107–120, 2022. ACM\n
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@inproceedings{DBLP:conf/middleware/CoxCD22,\n author = {Bart Cox and\n Lydia Y. Chen and\n J{\\'{e}}r{\\'{e}}mie Decouchant},\n editor = {Paolo Bellavista and\n Kaiwen Zhang and\n Abdelouahed Gherbi and\n Saurabh Bagchi and\n Marta Pati{\\~{n}}o and\n Giuseppe Di Modica and\n Julien Gascon{-}Samson},\n title = {Aergia: leveraging heterogeneity in federated learning systems},\n booktitle = {Middleware '22: 23rd International Middleware Conference, Quebec,\n QC, Canada, November 7 - 11, 2022},\n pages = {107--120},\n publisher = {{ACM}},\n year = {2022},\n url = {https://doi.org/10.1145/3528535.3565238},\n doi = {10.1145/3528535.3565238},\n timestamp = {Sun, 16 Apr 2023 01:00:00 +0200},\n biburl = {https://dblp.org/rec/conf/middleware/CoxCD22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n AGIC: Approximate Gradient Inversion Attack on Federated Learning.\n \n \n \n \n\n\n \n Xu, J.; Hong, C.; Huang, J.; Chen, L. Y.; and Decouchant, J.\n\n\n \n\n\n\n In
41st International Symposium on Reliable Distributed Systems, SRDS 2022, Vienna, Austria, September 19-22, 2022, pages 12–22, 2022. IEEE\n
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@inproceedings{DBLP:conf/srds/XuHHCD22,\n author = {Jin Xu and\n Chi Hong and\n Jiyue Huang and\n Lydia Y. Chen and\n J{\\'{e}}r{\\'{e}}mie Decouchant},\n title = {{AGIC:} Approximate Gradient Inversion Attack on Federated Learning},\n booktitle = {41st International Symposium on Reliable Distributed Systems, {SRDS}\n 2022, Vienna, Austria, September 19-22, 2022},\n pages = {12--22},\n publisher = {{IEEE}},\n year = {2022},\n url = {https://doi.org/10.1109/SRDS55811.2022.00012},\n doi = {10.1109/SRDS55811.2022.00012},\n timestamp = {Mon, 26 Jun 2023 01:00:00 +0200},\n biburl = {https://dblp.org/rec/conf/srds/XuHHCD22.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Attacks and Defenses for Free-Riders in Multi-Discriminator GAN.\n \n \n \n \n\n\n \n Zhao, Z.; Huang, J.; Roos, S.; and Chen, L. Y.\n\n\n \n\n\n\n
CoRR, abs/2201.09967. 2022.\n
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@article{DBLP:journals/corr/abs-2201-09967,\n author = {Zilong Zhao and\n Jiyue Huang and\n Stefanie Roos and\n Lydia Y. Chen},\n title = {Attacks and Defenses for Free-Riders in Multi-Discriminator {GAN}},\n journal = {CoRR},\n volume = {abs/2201.09967},\n year = {2022},\n url = {https://arxiv.org/abs/2201.09967},\n eprinttype = {arXiv},\n eprint = {2201.09967},\n timestamp = {Tue, 01 Feb 2022 00:00:00 +0100},\n biburl = {https://dblp.org/rec/journals/corr/abs-2201-09967.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n MEGA: Model Stealing via Collaborative Generator-Substitute Networks.\n \n \n \n \n\n\n \n Hong, C.; Huang, J.; and Chen, L. Y.\n\n\n \n\n\n\n
CoRR, abs/2202.00008. 2022.\n
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@article{DBLP:journals/corr/abs-2202-00008,\n author = {Chi Hong and\n Jiyue Huang and\n Lydia Y. Chen},\n title = {{MEGA:} Model Stealing via Collaborative Generator-Substitute Networks},\n journal = {CoRR},\n volume = {abs/2202.00008},\n year = {2022},\n url = {https://arxiv.org/abs/2202.00008},\n eprinttype = {arXiv},\n eprint = {2202.00008},\n timestamp = {Wed, 09 Feb 2022 00:00:00 +0100},\n biburl = {https://dblp.org/rec/journals/corr/abs-2202-00008.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Blind leads Blind: A Zero-Knowledge Attack on Federated Learning.\n \n \n \n \n\n\n \n Huang, J.; Zhao, Z.; Chen, L. Y.; and Roos, S.\n\n\n \n\n\n\n
CoRR, abs/2202.05877. 2022.\n
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@article{DBLP:journals/corr/abs-2202-05877,\n author = {Jiyue Huang and\n Zilong Zhao and\n Lydia Y. Chen and\n Stefanie Roos},\n title = {Blind leads Blind: {A} Zero-Knowledge Attack on Federated Learning},\n journal = {CoRR},\n volume = {abs/2202.05877},\n year = {2022},\n url = {https://arxiv.org/abs/2202.05877},\n eprinttype = {arXiv},\n eprint = {2202.05877},\n timestamp = {Fri, 18 Feb 2022 00:00:00 +0100},\n biburl = {https://dblp.org/rec/journals/corr/abs-2202-05877.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n CTAB-GAN+: Enhancing Tabular Data Synthesis.\n \n \n \n \n\n\n \n Zhao, Z.; Kunar, A.; Birke, R.; and Chen, L. Y.\n\n\n \n\n\n\n
CoRR, abs/2204.00401. 2022.\n
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@article{DBLP:journals/corr/abs-2204-00401,\n author = {Zilong Zhao and\n Aditya Kunar and\n Robert Birke and\n Lydia Y. Chen},\n title = {{CTAB-GAN+:} Enhancing Tabular Data Synthesis},\n journal = {CoRR},\n volume = {abs/2204.00401},\n year = {2022},\n url = {https://doi.org/10.48550/arXiv.2204.00401},\n doi = {10.48550/ARXIV.2204.00401},\n eprinttype = {arXiv},\n eprint = {2204.00401},\n timestamp = {Wed, 06 Apr 2022 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/corr/abs-2204-00401.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Federated Geometric Monte Carlo Clustering to Counter Non-IID Datasets.\n \n \n \n \n\n\n \n Lucchetti, F.; Decouchant, J.; Fernandes, M.; Chen, L. Y.; and Völp, M.\n\n\n \n\n\n\n
CoRR, abs/2204.11017. 2022.\n
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@article{DBLP:journals/corr/abs-2204-11017,\n author = {Federico Lucchetti and\n J{\\'{e}}r{\\'{e}}mie Decouchant and\n Maria Fernandes and\n Lydia Y. Chen and\n Marcus V{\\"{o}}lp},\n title = {Federated Geometric Monte Carlo Clustering to Counter Non-IID Datasets},\n journal = {CoRR},\n volume = {abs/2204.11017},\n year = {2022},\n url = {https://doi.org/10.48550/arXiv.2204.11017},\n doi = {10.48550/ARXIV.2204.11017},\n eprinttype = {arXiv},\n eprint = {2204.11017},\n timestamp = {Mon, 26 Jun 2023 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/corr/abs-2204-11017.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n AGIC: Approximate Gradient Inversion Attack on Federated Learning.\n \n \n \n \n\n\n \n Xu, J.; Hong, C.; Huang, J.; Chen, L. Y.; and Decouchant, J.\n\n\n \n\n\n\n
CoRR, abs/2204.13784. 2022.\n
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@article{DBLP:journals/corr/abs-2204-13784,\n author = {Jin Xu and\n Chi Hong and\n Jiyue Huang and\n Lydia Y. Chen and\n J{\\'{e}}r{\\'{e}}mie Decouchant},\n title = {{AGIC:} Approximate Gradient Inversion Attack on Federated Learning},\n journal = {CoRR},\n volume = {abs/2204.13784},\n year = {2022},\n url = {https://doi.org/10.48550/arXiv.2204.13784},\n doi = {10.48550/ARXIV.2204.13784},\n eprinttype = {arXiv},\n eprint = {2204.13784},\n timestamp = {Mon, 02 May 2022 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/corr/abs-2204-13784.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Targeted Influence with Community and Gender-Aware Seeding.\n \n \n \n \n\n\n \n Styczen, M.; Chen, B.; Teng, Y.; Pignolet, Y.; Chen, L. Y.; and Yang, D.\n\n\n \n\n\n\n
CoRR, abs/2208.12649. 2022.\n
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@article{DBLP:journals/corr/abs-2208-12649,\n author = {Maciej Styczen and\n Bing{-}Jyue Chen and\n Ya{-}Wen Teng and\n Yvonne{-}Anne Pignolet and\n Lydia Y. Chen and\n De{-}Nian Yang},\n title = {Targeted Influence with Community and Gender-Aware Seeding},\n journal = {CoRR},\n volume = {abs/2208.12649},\n year = {2022},\n url = {https://doi.org/10.48550/arXiv.2208.12649},\n doi = {10.48550/ARXIV.2208.12649},\n eprinttype = {arXiv},\n eprint = {2208.12649},\n timestamp = {Tue, 30 Aug 2022 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/corr/abs-2208-12649.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Aergia: Leveraging Heterogeneity in Federated Learning Systems.\n \n \n \n \n\n\n \n Cox, B.; Chen, L. Y.; and Decouchant, J.\n\n\n \n\n\n\n
CoRR, abs/2210.06154. 2022.\n
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@article{DBLP:journals/corr/abs-2210-06154,\n author = {Bart Cox and\n Lydia Y. Chen and\n J{\\'{e}}r{\\'{e}}mie Decouchant},\n title = {Aergia: Leveraging Heterogeneity in Federated Learning Systems},\n journal = {CoRR},\n volume = {abs/2210.06154},\n year = {2022},\n url = {https://doi.org/10.48550/arXiv.2210.06154},\n doi = {10.48550/ARXIV.2210.06154},\n eprinttype = {arXiv},\n eprint = {2210.06154},\n timestamp = {Tue, 18 Oct 2022 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/corr/abs-2210-06154.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Federated Learning for Tabular Data: Exploring Potential Risk to Privacy.\n \n \n \n \n\n\n \n Wu, H.; Zhao, Z.; Chen, L. Y.; and van Moorsel, A.\n\n\n \n\n\n\n
CoRR, abs/2210.06856. 2022.\n
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@article{DBLP:journals/corr/abs-2210-06856,\n author = {Han Wu and\n Zilong Zhao and\n Lydia Y. Chen and\n Aad van Moorsel},\n title = {Federated Learning for Tabular Data: Exploring Potential Risk to Privacy},\n journal = {CoRR},\n volume = {abs/2210.06856},\n year = {2022},\n url = {https://doi.org/10.48550/arXiv.2210.06856},\n doi = {10.48550/ARXIV.2210.06856},\n eprinttype = {arXiv},\n eprint = {2210.06856},\n timestamp = {Fri, 02 Aug 2024 01:00:00 +0200},\n biburl = {https://dblp.org/rec/journals/corr/abs-2210-06856.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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\n\n \n \n \n \n \n \n Permutation-Invariant Tabular Data Synthesis.\n \n \n \n \n\n\n \n Zhu, Y.; Zhao, Z.; Birke, R.; and Chen, L. Y.\n\n\n \n\n\n\n
CoRR, abs/2211.09286. 2022.\n
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@article{DBLP:journals/corr/abs-2211-09286,\n author = {Yujin Zhu and\n Zilong Zhao and\n Robert Birke and\n Lydia Y. Chen},\n title = {Permutation-Invariant Tabular Data Synthesis},\n journal = {CoRR},\n volume = {abs/2211.09286},\n year = {2022},\n url = {https://doi.org/10.48550/arXiv.2211.09286},\n doi = {10.48550/ARXIV.2211.09286},\n eprinttype = {arXiv},\n eprint = {2211.09286},\n timestamp = {Wed, 23 Nov 2022 00:00:00 +0100},\n biburl = {https://dblp.org/rec/journals/corr/abs-2211-09286.bib},\n bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n\n
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