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Main Authors: Jiang, Xin, Vandenberghe, Lieven
Format: Preprint
Published: 2022
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Online Access:https://arxiv.org/abs/2203.00252
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author Jiang, Xin
Vandenberghe, Lieven
author_facet Jiang, Xin
Vandenberghe, Lieven
contents The paper presents primal-dual proximal splitting methods for convex optimization, in which generalized Bregman distances are used to define the primal and dual proximal update steps. The methods extend the primal and dual Condat-Vu algorithms and the primal-dual three-operator (PD3O) algorithm. The Bregman extensions of the Condat-Vu algorithms are derived from the Bregman proximal point method applied to a monotone inclusion problem. Based on this interpretation, a unified framework for the convergence analysis of the two methods is presented. We also introduce a line search procedure for stepsize selection in the Bregman dual Condat-Vu algorithm applied to equality-constrained problems. Finally, we propose a Bregman extension of PD3O and analyze its convergence.
format Preprint
id arxiv_https___arxiv_org_abs_2203_00252
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Bregman three-operator splitting methods
Jiang, Xin
Vandenberghe, Lieven
Optimization and Control
The paper presents primal-dual proximal splitting methods for convex optimization, in which generalized Bregman distances are used to define the primal and dual proximal update steps. The methods extend the primal and dual Condat-Vu algorithms and the primal-dual three-operator (PD3O) algorithm. The Bregman extensions of the Condat-Vu algorithms are derived from the Bregman proximal point method applied to a monotone inclusion problem. Based on this interpretation, a unified framework for the convergence analysis of the two methods is presented. We also introduce a line search procedure for stepsize selection in the Bregman dual Condat-Vu algorithm applied to equality-constrained problems. Finally, we propose a Bregman extension of PD3O and analyze its convergence.
title Bregman three-operator splitting methods
topic Optimization and Control
url https://arxiv.org/abs/2203.00252