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Federated Learning
Paper List 본문
다음은 현재 읽고 있는, 혹은 읽을 예정인 paper 목록입니다. (읽은 것을 모두 포스팅하지는 않고, 선별하여 글을 작성합니다.) 목록은 지속적으로 update될 것이며, 현재로써는 CV나 NLP, Speech 등 특정 domain에 관련된 paper를 다룰 계획이 없습니다.
* 읽고 있는 paper
[ICML 2022] Data Condensation for Privacy Preserving
https://arxiv.org/abs/2206.00240
[S&P 2019] PixelDP
https://arxiv.org/abs/1802.03471
[IEEE TNSE 2022] FedMGDA+
https://arxiv.org/abs/2006.11489
[NeurIPS 2020] Gradient Clipping in Private SGD
https://arxiv.org/abs/2006.15429
[NeurIPS 2022] CalFAT
https://arxiv.org/abs/2205.14926
[ICLR 2023] MoCo
https://arxiv.org/abs/2210.12624
* 읽을 예정인 paper
[FL-NeurIPS 2022] FL Games
https://arxiv.org/abs/2205.11101
[ICML 2020] IRM Games
https://arxiv.org/abs/2002.04692
[NeurIPS 2021] Optimality and Stability in Federated Learning
https://arxiv.org/abs/2106.09580
[ICLR 2021] FedDyn
https://arxiv.org/abs/2111.04263
[AISTATS 2022] SparseFed
https://proceedings.mlr.press/v151/panda22a.html
[NeurIPS 2021] MIME
https://arxiv.org/abs/2008.03606
[AAAI 2021]S-FedAvg
https://ojs.aaai.org/index.php/AAAI/article/view/17093
[ICLR 2020] FedMA
https://arxiv.org/abs/2002.06440
[ICLR 2021] Bypassing the Ambient Dimension
https://arxiv.org/abs/2007.03813