Byzantine-Robust Gossip: Insights from a Dual Approach
Authors: Renaud Gaucher, Hadrien Hendrikx, Aymeric Dieuleveut | Published: 2024-05-06
Convergence Analysis
Exploring the Robustness of In-Context Learning with Noisy Labels
Authors: Chen Cheng, Xinzhi Yu, Haodong Wen, Jingsong Sun, Guanzhang Yue, Yihao Zhang, Zeming Wei | Published: 2024-04-28 | Updated: 2024-05-01
Federated Learning on Riemannian Manifolds with Differential Privacy
Authors: Zhenwei Huang, Wen Huang, Pratik Jawanpuria, Bamdev Mishra | Published: 2024-04-15
Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates
Authors: Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo | Published: 2024-03-18 | Updated: 2024-06-04
Bias-Aware Minimisation: Understanding and Mitigating Estimator Bias in Private SGD
Authors: Moritz Knolle, Robert Dorfman, Alexander Ziller, Daniel Rueckert, Georgios Kaissis | Published: 2023-08-23
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning
Authors: Edwige Cyffers, Aurélien Bellet, Debabrota Basu | Published: 2023-02-24 | Updated: 2023-07-12
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond
Authors: Meyer Scetbon, Elvis Dohmatob | Published: 2023-01-31
Quantization enabled Privacy Protection in Decentralized Stochastic Optimization
Authors: Yongqiang Wang, Tamer Basar | Published: 2022-08-07
Federated Stochastic Primal-dual Learning with Differential Privacy
Authors: Yiwei Li, Shuai Wang, Tsung-Hui Chang, Chong-Yung Chi | Published: 2022-04-26
An Equivalence Between Data Poisoning and Byzantine Gradient Attacks
Authors: Sadegh Farhadkhani, Rachid Guerraoui, Lê-Nguyên Hoang, Oscar Villemaud | Published: 2022-02-17 | Updated: 2022-07-20