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- Publisher Website: 10.1016/j.laa.2010.11.041
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Conference Paper: Solving a class of matrix minimization problems by linear variational inequality approaches
Title | Solving a class of matrix minimization problems by linear variational inequality approaches |
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Authors | |
Keywords | Projection and contraction method Matrix minimization |
Issue Date | 2011 |
Citation | Linear Algebra and Its Applications, 2011, v. 434, n. 11, p. 2343-2352 How to Cite? |
Abstract | A class of matrix optimization problems can be formulated as a linear variational inequalities with special structures. For solving such problems, the projection and contraction method (PC method) is extended to variational inequalities with matrix variables. Then the main costly computational load in PC method is to make a projection onto the semi-definite cone. Exploiting the special structures of the relevant variational inequalities, the Levenberg-Marquardt type projection and contraction method is advantageous. Preliminary numerical tests up to 1000Ã1000 matrices indicate that the suggested approach is promising. © 2011 Published by Elsevier Inc. |
Persistent Identifier | http://hdl.handle.net/10722/250967 |
ISSN | 2023 Impact Factor: 1.0 2023 SCImago Journal Rankings: 0.837 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Tao, Min | - |
dc.contributor.author | Yuan, Xiao Ming | - |
dc.contributor.author | He, Bing Sheng | - |
dc.date.accessioned | 2018-02-01T01:54:12Z | - |
dc.date.available | 2018-02-01T01:54:12Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Linear Algebra and Its Applications, 2011, v. 434, n. 11, p. 2343-2352 | - |
dc.identifier.issn | 0024-3795 | - |
dc.identifier.uri | http://hdl.handle.net/10722/250967 | - |
dc.description.abstract | A class of matrix optimization problems can be formulated as a linear variational inequalities with special structures. For solving such problems, the projection and contraction method (PC method) is extended to variational inequalities with matrix variables. Then the main costly computational load in PC method is to make a projection onto the semi-definite cone. Exploiting the special structures of the relevant variational inequalities, the Levenberg-Marquardt type projection and contraction method is advantageous. Preliminary numerical tests up to 1000Ã1000 matrices indicate that the suggested approach is promising. © 2011 Published by Elsevier Inc. | - |
dc.language | eng | - |
dc.relation.ispartof | Linear Algebra and Its Applications | - |
dc.subject | Projection and contraction method | - |
dc.subject | Matrix minimization | - |
dc.title | Solving a class of matrix minimization problems by linear variational inequality approaches | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.laa.2010.11.041 | - |
dc.identifier.scopus | eid_2-s2.0-79952624785 | - |
dc.identifier.volume | 434 | - |
dc.identifier.issue | 11 | - |
dc.identifier.spage | 2343 | - |
dc.identifier.epage | 2352 | - |
dc.identifier.isi | WOS:000289497700009 | - |
dc.identifier.issnl | 0024-3795 | - |