Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/7014
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | - |
dc.creator | Chen, X | - |
dc.creator | Niu, L | - |
dc.creator | Yuan, Y | - |
dc.date.accessioned | 2014-12-11T08:26:56Z | - |
dc.date.available | 2014-12-11T08:26:56Z | - |
dc.identifier.issn | 1052-6234 | - |
dc.identifier.uri | http://hdl.handle.net/10397/7014 | - |
dc.language.iso | en | en_US |
dc.publisher | Society for Industrial and Applied Mathematics | en_US |
dc.rights | © 2013 Society for Industrial and Applied Mathematics | en_US |
dc.subject | Nonsmooth nonconvex optimization | en_US |
dc.subject | Smoothing methods | en_US |
dc.subject | Convergence | en_US |
dc.subject | Regularized optimization | en_US |
dc.subject | Penalty function | en_US |
dc.subject | Non-Lipschitz | en_US |
dc.subject | Trust region Newton method | en_US |
dc.title | Optimality conditions and a smoothing trust region newton method for nonlipschitz optimization | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 1528 | - |
dc.identifier.epage | 1552 | - |
dc.identifier.volume | 23 | - |
dc.identifier.issue | 3 | - |
dc.identifier.doi | 10.1137/120871390 | - |
dcterms.abstract | Regularized minimization problems with nonconvex, nonsmooth, perhaps non-Lipschitz penalty functions have attracted considerable attention in recent years, owing to their wide applications in image restoration, signal reconstruction, and variable selection. In this paper, we derive affine-scaled second order necessary and sufficient conditions for local minimizers of such minimization problems. Moreover, we propose a global convergent smoothing trust region Newton method which can find a point satisfying the affine-scaled second order necessary optimality condition from any starting point. Numerical examples are given to demonstrate the effectiveness of the smoothing trust region Newton method. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | SIAM Journal on optimization, 2013, v. 23, no. 3, p. 1528–1552 | - |
dcterms.isPartOf | SIAM Journal on optimization | - |
dcterms.issued | 2013 | - |
dc.identifier.isi | WOS:000325094000007 | - |
dc.identifier.scopus | 2-s2.0-84886296616 | - |
dc.identifier.eissn | 1095-7189 | - |
dc.identifier.rosgroupid | r69606 | - |
dc.description.ros | 2013-2014 > Academic research: refereed > Publication in refereed journal | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Chen_Optimality_Smoothing_Trust.pdf | 313.61 kB | Adobe PDF | View/Open |
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