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Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/4606
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dc.contributor.authorGuo, Yien
dc.contributor.authorGao, Junbinen
dc.contributor.authorKwan, Paul Hingen
local.source.editorEditor(s): A Sattar and BH Kangen
dc.date.accessioned2010-02-12T15:26:00Z-
dc.date.issued2006-
dc.identifier.citationAI 2006: Advances in Artificial Intelligence, p. 1179-1183en
dc.identifier.isbn3540497870en
dc.identifier.isbn9783540497875en
dc.identifier.urihttps://hdl.handle.net/1959.11/4606-
dc.description.abstractIn this paper, we propose the Kernel Laplacian Eigenmaps for nonlinear dimensionality reduction. This method can be extended to any structured input beyond the usual vectorial data, enabling the visualization of a wider range of data in low dimension once suitable kernels are defined. Comparison with related methods based on MNIST handwritten digits data set supported the claim of our approach. In addition to nonlinear dimensionality reduction, this approach makes visualization and related applications on non-vectorial data possible.en
dc.languageenen
dc.publisherSpringeren
dc.relation.ispartofAI 2006: Advances in Artificial Intelligenceen
dc.relation.ispartofseriesLecture Notes in Computer Scienceen
dc.titleKernel Laplacian Eigenmaps for Visualization of Non-vectorial Dataen
dc.typeConference Publicationen
dc.relation.conferenceAI 2006: 19th Australian Joint Conference on Artificial Intelligenceen
dc.identifier.doi10.1007/11941439_144en
dc.subject.keywordsPattern Recognition and Data Miningen
local.contributor.firstnameYien
local.contributor.firstnameJunbinen
local.contributor.firstnamePaul Hingen
local.subject.for2008080109 Pattern Recognition and Data Miningen
local.subject.seo2008890299 Computer Software and Services not elsewhere classifieden
local.profile.schoolSchool of Science and Technologyen
local.profile.schoolSchool of Science and Technologyen
local.profile.emailyguo4@une.edu.auen
local.profile.emailwkwan2@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordpes:3373en
local.date.conference4th - 8th December, 2006en
local.conference.placeHobart, Australiaen
local.publisher.placeBerlin, Germanyen
local.format.startpage1179en
local.format.endpage1183en
local.series.issn1611-3349en
local.series.issn0302-9743en
local.series.number4304en
local.peerreviewedYesen
local.contributor.lastnameGuoen
local.contributor.lastnameGaoen
local.contributor.lastnameKwanen
local.seriespublisherSpringeren
local.seriespublisher.placeBerlin, Germanyen
dc.identifier.staffune-id:yguo4en
dc.identifier.staffune-id:wkwan2en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:4716en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleKernel Laplacian Eigenmaps for Visualization of Non-vectorial Dataen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.conference.detailsAI 2006: 19th Australian Joint Conference on Artificial Intelligence, Hobart, Australia, 4th - 8th December, 2006en
local.search.authorGuo, Yien
local.search.authorGao, Junbinen
local.search.authorKwan, Paul Hingen
local.uneassociationUnknownen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2006en
local.date.start2006-12-04-
local.date.end2006-12-08-
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