Title
Convergence rate of a proximal multiplier algorithm for separable convex minimization
Date Issued
01 February 2017
Access level
metadata only access
Resource Type
journal article
Author(s)
Publisher(s)
Taylor and Francis Ltd.
Abstract
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.
Start page
251
End page
270
Volume
66
Issue
2
Language
English
OCDE Knowledge area
Matemáticas aplicadas Matemáticas puras
Scopus EID
2-s2.0-84996553252
Source
Optimization
ISSN of the container
02331934
DOI of the container
10.1080/02331934.2016.1261138
Sources of information: Directorio de Producción Científica Scopus