Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

This article studies a class of nonsmooth decentralized multiagent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a common nonsmooth term. We propose a general primal-dual algorithmic framework that unifies many existing state-of-the-ar...

Full description

Bibliographic Details

Published in:	IEEE transactions on automatic control Vol. 66; no. 6; pp. 2787 - 2794
Main Authors:	Alghunaim, Sulaiman A., Ryu, Ernest K., Yuan, Kun, Sayed, Ali H.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.06.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Approximation algorithms Convergence Convex functions Cost function Decentralized optimization diffusion Electronic mail gradient tracking linear convergence Multiagent systems Optimization proximal gradient algorithms Symmetric matrices unified decentralized algorithm
ISSN:	0018-9286, 1558-2523
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!