A Distributed ADMM-like Method for Resource Sharing over Time-Varying Networks

DOI10.1137/17M1151973zbMath1427.90214arXiv1611.07393OpenAlexW2994958082WikidataQ126571596 ScholiaQ126571596MaRDI QIDQ5206938

Erfan Yazdandoost Hamedani, Necdet Serhat Aybat

Publication date: 19 December 2019

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1611.07393

zbMATH Keywords

convex optimizationprimal-dual methodconvergence ratemultiagent distributed optimizationresource sharing problem

Mathematics Subject Classification ID

Programming involving graphs or networks (90C35) Convex programming (90C25) Optimality conditions and duality in mathematical programming (90C46)

Related Items (8)

On iteration complexity of a first-order primal-dual method for nonlinear convex cone programming ⋮ Regularized dual gradient distributed method for constrained convex optimization over unbalanced directed graphs ⋮ Distributed delay-tolerant strategies for equality-constraint sum-preserving resource allocation ⋮ Decentralized optimization with affine constraints over time-varying networks ⋮ Privacy-preserving dual stochastic push-sum algorithm for distributed constrained optimization ⋮ Distributed convex optimization with coupling constraints over time-varying directed graphs ⋮ A Distributed ADMM-like Method for Resource Sharing over Time-Varying Networks ⋮ A Primal-Dual Algorithm with Line Search for General Convex-Concave Saddle Point Problems

Cites Work

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• On the ergodic convergence rates of a first-order primal-dual algorithm
• Distributed resource allocation on dynamic networks in quadratic time
• Subgradient methods for saddle-point problems
• Parallel multi-block ADMM with \(o(1/k)\) convergence
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Mirror Prox algorithm for multi-term composite minimization and semi-separable problems
• A First-Order Augmented Lagrangian Method for Compressed Sensing
• Convergence Analysis of Primal-Dual Algorithms for a Saddle-Point Problem: From Contraction Perspective
• 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
• Decentralized Resource Allocation in Dynamic Networks of Agents
• Distributed Linearized Alternating Direction Method of Multipliers for Composite Convex Consensus Optimization
• Multi-Agent Distributed Optimization via Inexact Consensus ADMM
• Consensus and Cooperation in Networked Multi-Agent Systems
• Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs
• A Distributed Algorithm for Resource Allocation Over Dynamic Digraphs
• A Proximal Dual Consensus ADMM Method for Multi-Agent Constrained Optimization
• Fastest Mixing Markov Chain on a Graph
• Collaborative Resource Allocation Over a Hybrid Cloud Center and Edge Server Network
• Distributed Subgradient Methods for Multi-Agent Optimization
• On Distributed Averaging Algorithms and Quantization Effects
• A Distributed ADMM-like Method for Resource Sharing over Time-Varying Networks
• Optimal Primal-Dual Methods for a Class of Saddle Point Problems
• Distributed Saddle-Point Subgradient Algorithms With Laplacian Averaging
• Compressed sensing

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