On the Optimal Step-size Selection for the Alternating Direction Method of Multipliers
2012 (English)Conference paper (Refereed)
The alternating direction method of multipliers is a powerful technique for structured large-scale optimization that has recently found applications in a variety of fields including networked optimization, estimation, compressed sensing and multi-agent systems. While applications of this technique have received a lot of attention, there is a lack of theoretical support for how to set the algorithm parameters, and its step-size is typically tuned experimentally. In this paper we consider three different formulations of the algorithm and present explicit expressions for the step-size that minimizes the convergence rate. We also compare our method with one of the existing step-size selection techniques for consensus applications.
Place, publisher, year, edition, pages
2012. 139-144 p.
Distributed and cooperative optimization, Multivehicle systems, flocking, and consensus
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-117618DOI: 10.3182/20120914-2-US-4030.00038ScopusID: 2-s2.0-84880998784OAI: oai:DiVA.org:kth-117618DiVA: diva2:602322
In Necsys2012: Proceeding of IFAC Workshop on Estimation and Control of Networked Systems
QC 201305212013-01-312013-01-312013-05-21Bibliographically approved