Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods

Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods

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 theoreti...

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Main Authors: Feng Ma, Mingfang Ni, Lei Zhu, Zhanke Yu
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/891017
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spelling doaj-0f0d441360cd4e5a80e281b5b8a1a2b72020-11-24T21:08:38ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/891017891017Sensitivity Analysis of the Proximal-Based Parallel Decomposition MethodsFeng Ma0Mingfang Ni1Lei Zhu2Zhanke Yu3College of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, ChinaCollege of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, ChinaCollege of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, ChinaCollege of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, ChinaThe 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.http://dx.doi.org/10.1155/2014/891017
collection DOAJ
language English
format Article
sources DOAJ
author Feng Ma
Mingfang Ni
Lei Zhu
Zhanke Yu
spellingShingle Feng Ma
Mingfang Ni
Lei Zhu
Zhanke Yu
Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods
Mathematical Problems in Engineering
author_facet Feng Ma
Mingfang Ni
Lei Zhu
Zhanke Yu
author_sort Feng Ma
title Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods
title_short Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods
title_full Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods
title_fullStr Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods
title_full_unstemmed Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods
title_sort sensitivity analysis of the proximal-based parallel decomposition methods
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2014-01-01
description 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.
url http://dx.doi.org/10.1155/2014/891017
work_keys_str_mv AT fengma sensitivityanalysisoftheproximalbasedparalleldecompositionmethods
AT mingfangni sensitivityanalysisoftheproximalbasedparalleldecompositionmethods
AT leizhu sensitivityanalysisoftheproximalbasedparalleldecompositionmethods
AT zhankeyu sensitivityanalysisoftheproximalbasedparalleldecompositionmethods
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