The Hidden Vulnerability of Distributed Learning in Byzantium

Authors: El Mahdi El Mhamdi, Rachid Guerraoui, Sébastien Rouault

Abstract

While machine learning is going through an era of celebrated success, concerns have been raised about the vulnerability of its backbone: stochastic gradient descent (SGD). Recent approaches have been proposed to ensure the robustness of distributed SGD against adversarial (Byzantine) workers sending

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