D-ADMM: A distributed algorithm for compressed sensing and other separable optimization problems

João F. C. Mota*, João M. F. Xavier, Pedro M. Q. Aguiar, Markus Püschel

*Corresponding author for this work

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

9 Citations (Scopus)

Abstract

We propose a distributed, decentralized algorithm for solving separable optimization problems over a connected network of compute nodes. In a separable problem, each node has its own private function and its own private constraint set. Private means that no other node has access to it. The goal is to minimize the sum of all nodes' private functions, constraining the solution to be in the intersection of all the private sets. Our algorithm is based on the alternating direction method of multipliers (ADMM) and requires a coloring of the network to be available beforehand. We perform numerical experiments of the algorithm, applying it to compressed sensing problems. These show that the proposed algorithm requires in general less iterations, and hence less communication between nodes, than previous algorithms to achieve a given accuracy.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
PublisherIEEE
Pages2869-2872
Number of pages4
ISBN (Electronic)9781467300469
ISBN (Print)9781467300452
DOIs
Publication statusPublished - 31 Aug 2012
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing - Kyoto, Japan
Duration: 25 Mar 201230 Mar 2012

Publication series

Name2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
PublisherIEEE
ISSN (Print)1520-6149
ISSN (Electronic)1520-6149

Conference

Conference2012 IEEE International Conference on Acoustics, Speech, and Signal Processing
Abbreviated titleICASSP 2012
Country/TerritoryJapan
CityKyoto
Period25/03/1230/03/12

Keywords

  • basis pursuit
  • compressed sensing
  • Distributed optimization
  • network optimization

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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