Convergence rate of a proximal multiplier algorithm for separable convex minimization

O. Sarmiento, E. A. Papa Quiroz, P. R. Oliveira

Research output: Contribution to journalArticle

Abstract

© 2016 Informa UK Limited, trading as Taylor & Francis Group. In this paper, we analyse the convergence rate of the proximal algorithm proposed by us in the article [A proximal multiplier method for separable convex minimization. Optimization. 2016; 65:501–537], which has been proposed to solve a separable convex minimization problem. We prove that, under mild assumptions, the primal-dual sequences of the algorithm converge linearly to the optimal solution for a class of proximal distances.
Original languageAmerican English
Pages (from-to)251-270
Number of pages20
JournalOptimization
DOIs
StatePublished - 1 Feb 2017

Fingerprint Dive into the research topics of 'Convergence rate of a proximal multiplier algorithm for separable convex minimization'. Together they form a unique fingerprint.

  • Cite this