Network Gradient Descent Algorithm for Decentralized Federated Learning

DOI10.1080/07350015.2022.2074426arXiv2205.08364OpenAlexW4229065521MaRDI QIDQ6190693

Shuyuan Wu, Danyang Huang, Hansheng Wang

Publication date: 6 March 2024

Published in: Journal of Business & Economic Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2205.08364

zbMATH Keywords

distributed systemgradient descentdeep learningdecentralized federated learning

Mathematics Subject Classification ID

Applications of statistics to economics (62P20)

Cites Work

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• Singularity, misspecification and the convergence rate of EM
• On the Convergence of Decentralized Gradient Descent
• Asymptotic Statistics
• Mathematical Statistics
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs
• Advances and Open Problems in Federated Learning
• An efficient multistep iteration scheme for systems of nonlinear algebraic equations associated with integral equations
• Communication-Efficient Distributed Statistical Inference

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