MULTI-AGENT CONSTRAINED OPTIMIZATION OF A STRONGLY CONVEX FUNCTION

被引：0

作者：

Hamedani, Erfan Yazdandoost ^{[1
]}

Aybat, Necdet Serhat ^{[1
]}

机构：

[1] Penn State Univ, Ind & Mfg Engn Dept, University Pk, PA 16802 USA

来源：

2017 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2017) | 2017年

关键词：

multi-agent distributed optimization; consensus; constrained optimization; convergence rate; NETWORKS; CONSENSUS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We consider cooperative multi-agent consensus optimization problems over an undirected network of agents, where only local communications are allowed. The objective is to minimize the sum of agent-specific convex functions over agentspecific private conic constraint sets. We provide convergence rates in sub-optimality, infeasibility and consensus violation when the sum function is strongly convex; examine the effect of underlying network topology on the convergence rates of the proposed decentralized algorithm.

引用

页码：558 / 562

页数：5

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