Communication-efficient and privacy-preserving large-scale federated learning counteracting heterogeneity

DOI10.1016/j.ins.2024.120167MaRDI QIDQ6126867

Xing-Cai Zhou, Guang Yang

Publication date: 10 April 2024

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

zbMATH Keywords

communication costsprivacy protectionfederated learningdata heterogeneitysystem heterogeneity

Mathematics Subject Classification ID

Computer science (68-XX) Operations research, mathematical programming (90-XX)

Cites Work

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• Communication-efficient algorithms for decentralized and stochastic optimization
• Rényi Divergence and Kullback-Leibler Divergence
• The Algorithmic Foundations of Differential Privacy
• Federated Variance-Reduced Stochastic Gradient Descent With Robustness to Byzantine Attacks
• Private stochastic convex optimization: optimal rates in linear time
• Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming

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