Convergence rate of a proximal multiplier algorithm for separable convex minimization

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

doi:10.1080/02331934.2016.1261138

Convergence rate of a proximal multiplier algorithm for separable convex minimization

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

Universidade Federal do Rio de Janeiro
Universidad Nacional Mayor de San Marcos

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

2 Citas (Scopus)

Resumen

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.

Idioma original	Inglés
Páginas (desde-hasta)	251-270
Número de páginas	20
Publicación	Optimization
Volumen	66
N.º	2
DOI	https://doi.org/10.1080/02331934.2016.1261138
Estado	Publicada - 1 feb. 2017
Publicado de forma externa	Sí

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title = "Convergence rate of a proximal multiplier algorithm for separable convex minimization",

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.",

keywords = "Proximal multiplier methods, convex functions, linear rate of convergence, proximal distances, separable convex problems",

author = "O. Sarmiento and \{Papa Quiroz\}, \{E. A.\} and Oliveira, \{P. R.\}",

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AU - Papa Quiroz, E. A.

AU - Oliveira, P. R.

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Y1 - 2017/2/1

N2 - 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.

AB - 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.

KW - Proximal multiplier methods

KW - convex functions

KW - linear rate of convergence

KW - proximal distances

KW - separable convex problems

UR - https://www.scopus.com/pages/publications/84996553252

U2 - 10.1080/02331934.2016.1261138

DO - 10.1080/02331934.2016.1261138

M3 - Article

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SP - 251

EP - 270

JO - Optimization

JF - Optimization

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Convergence rate of a proximal multiplier algorithm for separable convex minimization

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