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Cited 6 time in webofscience Cited 7 time in scopus
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dc.contributor.authorKim, HC-
dc.contributor.authorLee, J-
dc.date.accessioned2016-04-01T01:55:01Z-
dc.date.available2016-04-01T01:55:01Z-
dc.date.created2009-02-28-
dc.date.issued2006-01-
dc.identifier.issn0302-9743-
dc.identifier.other2006-OAK-0000005978-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/23993-
dc.description.abstractGaussian processes (GP) provide a kernel machine framework. They have been mainly applied to regression and classification. We propose a pseudo-density estimation method based on the information of variance functions of GPs, which relates to the density of the data points. We also show how the constructed pseudo-density can be applied to clustering. Through simulation we show that the topology of the pseudo-density represents the clustering information well with promising results.-
dc.description.statementofresponsibilityX-
dc.languageEnglish-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.relation.isPartOfLECTURE NOTES IN COMPUTER SCIENCE-
dc.titlePseudo-density estimation for clustering with Gaussian processes-
dc.typeArticle-
dc.contributor.college산업경영공학과-
dc.identifier.doi10.1007/11759966_183-
dc.author.googleKim, HC-
dc.author.googleLee, J-
dc.relation.volume3971-
dc.relation.startpage1238-
dc.relation.lastpage1243-
dc.contributor.id10081901-
dc.relation.journalLECTURE NOTES IN COMPUTER SCIENCE-
dc.relation.indexSCI급, SCOPUS 등재논문-
dc.relation.sciSCIE-
dc.collections.nameConference Papers-
dc.type.rimsART-
dc.identifier.bibliographicCitationLECTURE NOTES IN COMPUTER SCIENCE, v.3971, pp.1238 - 1243-
dc.identifier.wosid000238112000183-
dc.date.tcdate2019-01-01-
dc.citation.endPage1243-
dc.citation.startPage1238-
dc.citation.titleLECTURE NOTES IN COMPUTER SCIENCE-
dc.citation.volume3971-
dc.contributor.affiliatedAuthorLee, J-
dc.identifier.scopusid2-s2.0-33745913334-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.wostc5-
dc.type.docTypeArticle; Proceedings Paper-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-

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이재욱LEE, JAEWOOK
Dept of Industrial & Management Enginrg
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