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Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent.

POMACS, no. 2 (2019)

Cited by: 150|Views150
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Abstract

We consider the distributed statistical learning problem over decentralized systems that are prone to adversarial attacks. This setup arises in many practical applications, including Google's Federated Learning. Formally, we focus on a decentralized system that consists of a parameter server and m working machines; each working machine ke...More

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