1. Research UNE
  2. UNE
  3. Conference Publication
Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/1021
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGuo, Yen
dc.contributor.authorGao, Jen
dc.contributor.authorKwan, PHen
local.source.editorEditor(s): K-L Ong, K Smith-Miles, V Lee, & W-K Ngen
dc.date.accessioned2008-09-25T15:03:00Z-
dc.date.issued2006-
dc.identifier.citationProceedings of The 2006 International Workshop on Integrating AI and Data Mining (AIDM'06), p. 11-17en
dc.identifier.isbn0769527302en
dc.identifier.urihttps://hdl.handle.net/1959.11/1021-
dc.description.abstractVisualization of non-vectorial objects is not easy in practicedue to their lack of convenient vectorial representation.Representative approaches are Kernel PCA and KernelLaplacian Eigenmaps introduced recently in our research.Extending our earlier work, we propose in this papera new algorithm called Twin Kernel Embedding (TKE)that preserves the similarity structure of input data in the latentspace. Experimental evaluation on MNIST handwrittendigit database verifies that TKE outperforms related methods.en
dc.languageenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.ispartofProceedings of The 2006 International Workshop on Integrating AI and Data Mining (AIDM'06)en
dc.titleVisualization of Non-vectorial Data Using Twin Kernel Embeddingen
dc.typeConference Publicationen
dc.relation.conferenceAIDM 2006: International Workshop on Integrating AI and Data Miningen
dc.identifier.doi10.1109/AIDM.2006.18en
dc.subject.keywordsPattern Recognition and Data Miningen
local.contributor.firstnameYen
local.contributor.firstnameJen
local.contributor.firstnamePHen
local.subject.for2008080109 Pattern Recognition and Data Miningen
local.subject.seo700199 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:4266en
local.date.conference4th - 8th December, 2006en
local.conference.placeHobart, Australiaen
local.publisher.placeLos Alamitos, United States of Americaen
local.format.startpage11en
local.format.endpage17en
local.peerreviewedYesen
local.contributor.lastnameGuoen
local.contributor.lastnameGaoen
local.contributor.lastnameKwanen
dc.identifier.staffune-id:yguo4en
dc.identifier.staffune-id:wkwan2en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1040en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleVisualization of Non-vectorial Data Using Twin Kernel Embeddingen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.conference.detailsAIDM 2006: International Workshop on Integrating AI and Data Mining, Hobart, Australia, 4th - 8th December, 2006en
local.search.authorGuo, Yen
local.search.authorGao, Jen
local.search.authorKwan, PHen
local.uneassociationUnknownen
local.year.published2006en
local.date.start2006-12-04-
local.date.end2006-12-08-
Appears in Collections:Conference Publication
Files in This Item:
2 files
File Description SizeFormat 
Show simple item record

SCOPUSTM   
Citations

12
checked on Dec 14, 2024

Page view(s)

1,108
checked on Dec 15, 2024
Google Media

Google ScholarTM

Check

Altmetric


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.