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dc.contributor.convenorAndrew Bradley
dc.contributor.authorLi, H
dc.contributor.authorGao, Y
dc.contributor.authorSun, J
dc.contributor.editorIEEE
dc.date.accessioned2017-05-03T15:01:12Z
dc.date.available2017-05-03T15:01:12Z
dc.date.issued2011
dc.date.modified2012-02-20T05:51:30Z
dc.identifier.isbn9780769545882
dc.identifier.refurihttp://itee.uq.edu.au/~dicta2011/
dc.identifier.doi10.1109/DICTA.2011.20
dc.identifier.urihttp://hdl.handle.net/10072/42997
dc.description.abstractTwo efficient algorithms are proposed to seek the sparse representation on high-dimensional Hilbert space. By proving that all the calculations in Orthogonal Match Pursuit (OMP) are essentially inner-product combinations, we modify the OMP algorithm to apply the kernel-trick. The proposed Kernel OMP (KOMP) is much faster than the existing methods, and illustrates higher accuracy in some scenarios. Furthermore, inspired by the success of group-sparsity, we enforce a rigid group-sparsity constraint on KOMP which leads to a noniterative variation. The constrained cousin of KOMP, dubbed as Single-Step KOMP (S-KOMP), merely takes one step to achieve the sparse coefficients. A remarkable improvement (up to 2,750 times) in efficiency is reported for S-KOMP, with only a negligible loss of accuracy.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.publisherIEEE Computer Society
dc.publisher.placeLos Alamitos, CA, USA
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencename2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011)
dc.relation.ispartofconferencetitleProceedings - 2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011
dc.relation.ispartofdatefrom2011-12-06
dc.relation.ispartofdateto2011-12-08
dc.relation.ispartoflocationNoosa, Queensland, Australia
dc.relation.ispartofpagefrom72
dc.relation.ispartofpageto77
dc.rights.retentionY
dc.subject.fieldofresearchComputer vision
dc.subject.fieldofresearchcode460304
dc.titleFast Kernel Sparse Representation
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.date.issued2011
gro.hasfulltextNo Full Text
gro.griffith.authorGao, Yongsheng


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    Contains papers delivered by Griffith authors at national and international conferences.

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