Byzantine-robust variance-reduced federated learning over distributed non-i.i.d. data

DOI10.1016/j.ins.2022.10.120arXiv2009.08161MaRDI QIDQ6125188

Tianyi Chen, Jie Peng, Qing Ling, Zhaoxian Wu

Publication date: 11 April 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2009.08161

zbMATH Keywords

variance reductiondistributed optimizationfederated learningnon-i.i.d. dataByzantine attacks

Mathematics Subject Classification ID

Computer science (68-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Cites Work

• On the point for which the sum of the distances to \(n\) given points is minimum
• EGC: entropy-based gradient compression for distributed deep learning
• Large-Scale Machine Learning with Stochastic Gradient Descent
• The Byzantine Generals Problem
• Federated Variance-Reduced Stochastic Gradient Descent With Robustness to Byzantine Attacks
• Distributed Approximate Newton's Method Robust to Byzantine Attackers

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