On semidefinite bounds for maximization of a non-convex quadratic objective over the ℓ1 unit ball
dc.citation.epage | 265 | en_US |
dc.citation.issueNumber | 3 | en_US |
dc.citation.spage | 253 | en_US |
dc.citation.volumeNumber | 40 | en_US |
dc.contributor.author | Pınar, M. Ç. | en_US |
dc.contributor.author | Teboulle, M. | en_US |
dc.date.accessioned | 2016-02-08T10:18:57Z | |
dc.date.available | 2016-02-08T10:18:57Z | |
dc.date.issued | 2006 | en_US |
dc.department | Department of Industrial Engineering | en_US |
dc.description.abstract | We consider the non-convex quadratic maximization problem subject to the ℓ1 unit ball constraint. The nature of the l1 norm structure makes this problem extremely hard to analyze, and as a consequence, the same difficulties are encountered when trying to build suitable approximations for this problem by some tractable convex counterpart formulations. We explore some properties of this problem, derive SDP-like relaxations and raise open questions. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T10:18:57Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2006 | en |
dc.identifier.doi | 10.1051/ro:2006023 | en_US |
dc.identifier.eissn | 1290-3868 | |
dc.identifier.issn | 0399-0559 | |
dc.identifier.uri | http://hdl.handle.net/11693/23775 | |
dc.language.iso | English | en_US |
dc.publisher | E D P Sciences | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1051/ro:2006023 | en_US |
dc.source.title | RAIRO - Operations Research | en_US |
dc.subject | Non-convex quadratic optimization | en_US |
dc.subject | L1-norm constraint | en_US |
dc.subject | Semidefinite programming relaxation | en_US |
dc.subject | Duality | en_US |
dc.title | On semidefinite bounds for maximization of a non-convex quadratic objective over the ℓ1 unit ball | en_US |
dc.type | Article | en_US |
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