Gradient Obfuscation Gives a False Sense of Security in Federated Learning
Authors: Kai Yue, Richeng Jin, Chau-Wai Wong, Dror Baron, Huaiyu Dai | Published: 2022-06-08 | Updated: 2022-10-14
Dap-FL: Federated Learning flourishes by adaptive tuning and secure aggregation
Authors: Qian Chen, Zilong Wang, Jiawei Chen, Haonan Yan, Xiaodong Lin | Published: 2022-06-08
Rate Distortion Tradeoff in Private Read Update Write in Federated Submodel Learning
Authors: Sajani Vithana, Sennur Ulukus | Published: 2022-06-07
Group privacy for personalized federated learning
Authors: Filippo Galli, Sayan Biswas, Kangsoo Jung, Tommaso Cucinotta, Catuscia Palamidessi | Published: 2022-06-07 | Updated: 2022-09-04
Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?
Authors: Huiyu Li, Nicholas Ayache, Hervé Delingette | Published: 2022-06-07
Building Robust Ensembles via Margin Boosting
Authors: Dinghuai Zhang, Hongyang Zhang, Aaron Courville, Yoshua Bengio, Pradeep Ravikumar, Arun Sai Suggala | Published: 2022-06-07
Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples
Authors: Dongyoon Yang, Insung Kong, Yongdai Kim | Published: 2022-06-07 | Updated: 2023-06-01
Subject Membership Inference Attacks in Federated Learning
Authors: Anshuman Suri, Pallika Kanani, Virendra J. Marathe, Daniel W. Peterson | Published: 2022-06-07 | Updated: 2023-06-02
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning
Authors: Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Zhongliang Yang, Yongfeng Huang, Xing Xie | Published: 2022-06-07 | Updated: 2022-10-31
Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization
Authors: Aniket Das, Bernhard Schölkopf, Michael Muehlebach | Published: 2022-06-07 | Updated: 2022-10-10