Optimal distributed stochastic mirror descent for strongly convex optimization

DOI10.1016/j.automatica.2017.12.053zbMath1387.93190arXiv1610.04702OpenAlexW2964191394MaRDI QIDQ1640744

Daniel W. C. Ho, Deming Yuan, Yiguang Hong, Guo-Ping Jiang

Publication date: 14 June 2018

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1610.04702

zbMATH Keywords

optimal convergence ratestrong convexitymirror descentdistributed stochastic optimizationepoch gradient descentnon-Euclidean divergence

Mathematics Subject Classification ID

Stochastic programming (90C15) Optimal stochastic control (93E20) Agent technology and artificial intelligence (68T42)

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Cites Work

• Initialization-free distributed algorithms for optimal resource allocation with feasibility constraints and application to economic dispatch of power systems
• Distributed stochastic subgradient projection algorithms for convex optimization
• Distributed multi-agent optimization subject to nonidentical constraints and communication delays
• Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication
• Mirror descent and nonlinear projected subgradient methods for convex optimization.
• On Convergence Rate of Distributed Stochastic Gradient Algorithm for Convex Optimization with Inequality Constraints
• An optimal algorithm for stochastic strongly-convex optimization
• Stochastic Gradient-Push for Strongly Convex Functions on Time-Varying Directed Graphs
• Distributed Optimization Over Time-Varying Directed Graphs
• Distributed Constrained Optimization by Consensus-Based Primal-Dual Perturbation Method
• Robust Stochastic Approximation Approach to Stochastic Programming
• Diffusion Adaptation Strategies for Distributed Optimization and Learning Over Networks
• Distributed Subgradient Methods for Multi-Agent Optimization
• Constrained Consensus and Optimization in Multi-Agent Networks
• EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization
• Gossip Algorithms for Convex Consensus Optimization Over Networks
• On Distributed Convex Optimization Under Inequality and Equality Constraints
• Understanding Machine Learning