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Article: A proximal strictly contractive Peacemanâ Rachford splitting method for convex programming with applications to imaging
Title | A proximal strictly contractive Peacemanâ Rachford splitting method for convex programming with applications to imaging |
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Authors | |
Keywords | Contraction Convergence rate Convex programming Peacemanâ Rachford splitting method Image processing |
Issue Date | 2015 |
Publisher | Society for Industrial and Applied Mathematics. The Journal's web site is located at http://www.siam.org/journals/siims.php |
Citation | SIAM Journal on Imaging Sciences, 2015, v. 8, n. 2, p. 1332-1365 How to Cite? |
Abstract | © 2015 Society for Industrial and Applied Mathematics. A strictly contractive Peacemanâ Rachford splitting method was proposed recently for solving separable convex programming problems. In this paper we further discuss a proximal version of this method, where a subproblem at each iteration is regularized by a proximal point term. The resulting regularized subproblem thus may have closed-form or easily computable solutions, especially in some interesting applications such as a class of sparse and low-rank optimization models. We establish the worst-case convergence rate measured by the iteration complexity in both the ergodic and nonergodic senses for the new algorithm. Some applications arising in image processing are tested to demonstrate the efficiency of the new algorithm. |
Persistent Identifier | http://hdl.handle.net/10722/251111 |
ISSN | 2023 Impact Factor: 2.1 2023 SCImago Journal Rankings: 0.960 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, Xinxin | - |
dc.contributor.author | Yuan, Xiaoming | - |
dc.date.accessioned | 2018-02-01T01:54:36Z | - |
dc.date.available | 2018-02-01T01:54:36Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | SIAM Journal on Imaging Sciences, 2015, v. 8, n. 2, p. 1332-1365 | - |
dc.identifier.issn | 1936-4954 | - |
dc.identifier.uri | http://hdl.handle.net/10722/251111 | - |
dc.description.abstract | © 2015 Society for Industrial and Applied Mathematics. A strictly contractive Peacemanâ Rachford splitting method was proposed recently for solving separable convex programming problems. In this paper we further discuss a proximal version of this method, where a subproblem at each iteration is regularized by a proximal point term. The resulting regularized subproblem thus may have closed-form or easily computable solutions, especially in some interesting applications such as a class of sparse and low-rank optimization models. We establish the worst-case convergence rate measured by the iteration complexity in both the ergodic and nonergodic senses for the new algorithm. Some applications arising in image processing are tested to demonstrate the efficiency of the new algorithm. | - |
dc.language | eng | - |
dc.publisher | Society for Industrial and Applied Mathematics. The Journal's web site is located at http://www.siam.org/journals/siims.php | - |
dc.relation.ispartof | SIAM Journal on Imaging Sciences | - |
dc.subject | Contraction | - |
dc.subject | Convergence rate | - |
dc.subject | Convex programming | - |
dc.subject | Peacemanâ Rachford splitting method | - |
dc.subject | Image processing | - |
dc.title | A proximal strictly contractive Peacemanâ Rachford splitting method for convex programming with applications to imaging | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1137/14099509X | - |
dc.identifier.scopus | eid_2-s2.0-84936755413 | - |
dc.identifier.volume | 8 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 1332 | - |
dc.identifier.epage | 1365 | - |
dc.identifier.isi | WOS:000357405500020 | - |
dc.identifier.issnl | 1936-4954 | - |