Parallel multi-splitting proximal method for star networks

Ermin Wei*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We develop a parallel algorithm based on proximal method to solve the problem of minimizing summation of convex (not necessarily smooth) functions over a star network. We show that this method converges to an optimal solution for any choice of constant stepsize for convex objective functions. Under further assumption of Lipschitz-gradient and strong convexity of objective functions, the method converges linearly.

Original languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4341-4346
Number of pages6
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Other

Other2017 American Control Conference, ACC 2017
CountryUnited States
CitySeattle
Period5/24/175/26/17

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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