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Article: Linearized alternating direction method of multipliers for constrained linear least-squares problem

TitleLinearized alternating direction method of multipliers for constrained linear least-squares problem
Authors
KeywordsLinearization
Alternating direction method of multipliers
Image processing
Linear least-squares problems
Issue Date2012
Citation
East Asian Journal on Applied Mathematics, 2012, v. 2, n. 4, p. 326-341 How to Cite?
AbstractThe alternating direction method of multipliers (ADMM) is applied to a constrained linear least-squares problem, where the objective function is a sum of two least-squares terms and there are box constraints. The original problem is decomposed into two easier least-squares subproblems at each iteration, and to speed up the inner iteration we linearize the relevant subproblem whenever it has no known closed-form solution. We prove the convergence of the resulting algorithm, and apply it to solve some image deblurring problems. Its efficiency is demonstrated, in comparison with Newton-type methods. © 2012 Global-Science Press.
Persistent Identifierhttp://hdl.handle.net/10722/251265
ISSN
2023 Impact Factor: 1.2
2023 SCImago Journal Rankings: 0.420
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChan, Raymond H.-
dc.contributor.authorTao, Min-
dc.contributor.authorYuan, Xiaoming-
dc.date.accessioned2018-02-01T01:55:03Z-
dc.date.available2018-02-01T01:55:03Z-
dc.date.issued2012-
dc.identifier.citationEast Asian Journal on Applied Mathematics, 2012, v. 2, n. 4, p. 326-341-
dc.identifier.issn2079-7362-
dc.identifier.urihttp://hdl.handle.net/10722/251265-
dc.description.abstractThe alternating direction method of multipliers (ADMM) is applied to a constrained linear least-squares problem, where the objective function is a sum of two least-squares terms and there are box constraints. The original problem is decomposed into two easier least-squares subproblems at each iteration, and to speed up the inner iteration we linearize the relevant subproblem whenever it has no known closed-form solution. We prove the convergence of the resulting algorithm, and apply it to solve some image deblurring problems. Its efficiency is demonstrated, in comparison with Newton-type methods. © 2012 Global-Science Press.-
dc.languageeng-
dc.relation.ispartofEast Asian Journal on Applied Mathematics-
dc.subjectLinearization-
dc.subjectAlternating direction method of multipliers-
dc.subjectImage processing-
dc.subjectLinear least-squares problems-
dc.titleLinearized alternating direction method of multipliers for constrained linear least-squares problem-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.4208/eajam.270812.161112a-
dc.identifier.scopuseid_2-s2.0-84894669445-
dc.identifier.volume2-
dc.identifier.issue4-
dc.identifier.spage326-
dc.identifier.epage341-
dc.identifier.eissn2079-7370-
dc.identifier.isiWOS:000325517100004-
dc.identifier.issnl2079-7362-

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