Federated dual averaging learning algorithm with delayed gradients for composite optimization

DOI10.1016/j.ins.2024.121223MaRDI QIDQ6658933

Jia Wang, Yu-Qi Hao, Jueyou Li

Publication date: 8 January 2025

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

zbMATH Keywords

dual averagingcomposite optimizationfederated learningdelayed gradients

Mathematics Subject Classification ID

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

Cites Work

• Sparse inverse covariance estimation with the graphical lasso
• Distributed optimization for multi-agent systems with constraints set and communication time-delay over a directed graph
• Exact matrix completion via convex optimization
• An Asynchronous Mini-Batch Algorithm for Regularized Stochastic Optimization
• Regression Shrinkage and Selection via The Lasso: A Retrospective
• Decentralized Consensus Algorithm with Delayed and Stochastic Gradients
• Regularization and Variable Selection Via the Elastic Net
• Communication-efficient and privacy-preserving large-scale federated learning counteracting heterogeneity
• Online distributed dual averaging algorithm for multi-agent bandit optimization over time-varying general directed networks
• RTGA: robust ternary gradients aggregation for federated learning

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