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.
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页数：5
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