Stochastic mirror descent method for distributed multi-agent optimization
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Publication:1670526
DOI10.1007/s11590-016-1071-zzbMath1405.90036OpenAlexW2512769831MaRDI QIDQ1670526
Guoquan Li, Jueyou Li, Changzhi Wu, Zhi-You Wu
Publication date: 5 September 2018
Published in: Optimization Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11590-016-1071-z
Convex programming (90C25) Stochastic programming (90C15) Deterministic network models in operations research (90B10)
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Cites Work
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- On stochastic gradient and subgradient methods with adaptive steplength sequences
- Distributed stochastic subgradient projection algorithms for convex optimization
- Distributed average consensus with least-mean-square deviation
- Mirror descent and nonlinear projected subgradient methods for convex optimization.
- The effect of deterministic noise in subgradient methods
- Gradient-free method for nonsmooth distributed optimization
- Randomized Smoothing for Stochastic Optimization
- Incremental Stochastic Subgradient Algorithms for Convex Optimization
- A Randomized Incremental Subgradient Method for Distributed Optimization in Networked Systems
- Robust Stochastic Approximation Approach to Stochastic Programming
- Distributed asynchronous deterministic and stochastic gradient optimization algorithms
- Distributed Subgradient Methods for Multi-Agent Optimization
- Constrained Consensus and Optimization in Multi-Agent Networks
- On Stochastic Subgradient Mirror-Descent Algorithm with Weighted Averaging
- DISTRIBUTED PROXIMAL-GRADIENT METHOD FOR CONVEX OPTIMIZATION WITH INEQUALITY CONSTRAINTS
- Consensus Problems in Networks of Agents With Switching Topology and Time-Delays
- Distributed Subgradient Methods for Convex Optimization Over Random Networks
- On Distributed Convex Optimization Under Inequality and Equality Constraints
- Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling
- Convergence of a Multi-Agent Projected Stochastic Gradient Algorithm for Non-Convex Optimization
- Distributed primal–dual stochastic subgradient algorithms for multi‐agent optimization under inequality constraints