Person
Rafaël Benjamin Pinot
This person is no longer with EPFL
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Related publications (11)
Please note that this is not a complete list of this person’s publications. It includes only semantically relevant works. For a full list, please refer to Infoscience.
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity
Rachid Guerraoui, Nirupam Gupta, John Stephan, Sadegh Farhadkhani, Youssef Allouah, Rafaël Benjamin Pinot
Byzantine machine learning (ML) aims to ensure the resilience of distributed learning algorithms to misbehaving (or Byzantine) machines. Although this problem received significant attention, prior works often assume the data held by the machines to be homo ...
PMLR2023On the Privacy-Robustness-Utility Trilemma in Distributed Learning
Rachid Guerraoui, Nirupam Gupta, John Stephan, Youssef Allouah, Rafaël Benjamin Pinot
The ubiquity of distributed machine learning (ML) in sensitive public domain applications calls for algorithms that protect data privacy, while being robust to faults and adversarial behaviors. Although privacy and robustness have been extensively studied ...
2023Robust Collaborative Learning with Linear Gradient Overhead
Rachid Guerraoui, Nirupam Gupta, John Stephan, Sadegh Farhadkhani, Le Nguyen Hoang, Rafaël Benjamin Pinot
Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...
PLMR2023