Spectral-like gradient method for distributed optimization

被引：0

作者：

Jakovetic, Dusan ^{[1
]}

Krejic, Natasa ^{[1
]}

Jerinkic, Natasa Krklec ^{[1
]}

机构：

[1] Univ Novi Sad, Fac Sci, Dept Math & Informat, Novi Sad, Serbia

来源：

PROCEEDINGS OF 18TH INTERNATIONAL CONFERENCE ON SMART TECHNOLOGIES (IEEE EUROCON 2019) | 2019年

关键词：

Distributed optimization; Consensus optimization; Spectral gradient method; Barzilai-Borwein method; BARZILAI; CONSENSUS;

D O I：

10.1109/eurocon.2019.8861761

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 a standard distributed multi-agent optimization setting where n nodes (agents) in a network minimize the aggregate sum of their local convex cost functions. We present a distributed spectral-like gradient method, wherein step sizes are node- and iteration-varying, and they are inspired by classical spectral methods from centralized optimization. Simulation examples illustrate the performance of the presented method.

引用

页数：5

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