Sensitivity analysis of the proximal-based parallel decomposition methods
type: Item
instance of: scholarly article
title: Sensitivity analysis of the proximal-based parallel decomposition methods
zbMATH Open document ID: 1407.90255
DOI: 10.1155/2014/891017
author: Feng Ma
author: Lei Zhu
author: Zhanke Yu
author: Mingfang Ni
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: The proximal-based parallel decomposition methods were recently proposed to solve structured convex optimization problems. These algorithms are eligible for parallel computation and can be used efficiently for solving large-scale separable problems. In this paper, compared with the previous theoretical results, we show that the range of the involved parameters can be enlarged while the convergence can be still established. Preliminary numerical tests on stable principal component pursuit problem testify to the advantages of the enlargement.
Mathematics Subject Classification ID: 90C25
Mathematics Subject Classification ID: 90C33
zbMATH DE Number: 7017517
Wikidata QID: Q59070401
describes a project that uses: UNLocBoX
describes a project that uses: RecPF
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/891017
OpenAlex ID: W2029490716
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description: scientific article; zbMATH DE number 7017517