Collaborative Learning as an Agreement Problem. - El-Mahdi El-Mhamdi; Sadegh Farhadkhani; Rachid Guerraoui; Arsany Guirguis; Lê Nguyên Hoang; Sébastien Rouault (CoRR, 2020)

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning). - El-Mahdi El-Mhamdi; Sadegh Farhadkhani; Rachid Guerraoui; Arsany Guirguis; Lê-Nguyên Hoang; Sébastien Rouault (NeurIPS, 2021)

Strategyproof Learning: Building Trustworthy User-Generated Datasets. - Sadegh Farhadkhani; Rachid Guerraoui; Lê-Nguyên Hoang (CoRR, 2021)

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums. - Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; John Stephan (ICML, 2022)

An Equivalence Between Data Poisoning and Byzantine Gradient Attacks. - Sadegh Farhadkhani; Rachid Guerraoui; Lê Nguyên Hoang; Oscar Villemaud (ICML, 2022)

Making Byzantine Decentralized Learning Efficient. - Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Lê Nguyên Hoang; Rafael Pinot; John Stephan (CoRR, 2022)

On the Impossible Safety of Large AI Models. - El-Mahdi El-Mhamdi; Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Lê-Nguyên Hoang; Rafael Pinot; John Stephan (CoRR, 2022)

Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity. - Youssef Allouah; Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; John Stephan (AISTATS, 2023)

On the Strategyproofness of the Geometric Median. - El-Mahdi El-Mhamdi; Sadegh Farhadkhani; Rachid Guerraoui; Lê-Nguyên Hoang (AISTATS, 2023)

Robust Collaborative Learning with Linear Gradient Overhead. - Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Lê-Nguyên Hoang; Rafael Pinot; John Stephan (ICML, 2023)

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication. - Martijn de Vos; Sadegh Farhadkhani; Rachid Guerraoui; Anne-Marie Kermarrec; Rafael Pires 001; Rishi Sharma 001 (NeurIPS, 2023)

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons. - Julien Fageot; Sadegh Farhadkhani; Lê-Nguyên Hoang; Oscar Villemaud (AAAI, 2024)

Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates. - Youssef Allouah; Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; Geovani Rizk; Sasha Voitovych (ICML, 2024)

Brief Announcement: A Case for Byzantine Machine Learning. - Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot (PODC, 2024)

Tackling Byzantine Clients in Federated Learning. - Youssef Allouah; Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot; Geovani Rizk; Sasha Voitovych (CoRR, 2024)

On the Relevance of Byzantine Robust Optimization Against Data Poisoning. - Sadegh Farhadkhani; Rachid Guerraoui; Nirupam Gupta; Rafael Pinot (CoRR, 2024)