Using dependencies to pair samples for multi-view learning

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorTripathi, Abhishek
dc.contributor.authorKlami, Arto
dc.contributor.authorKaski, Samuel
dc.contributor.departmentDepartment of Information and Computer Scienceen
dc.contributor.departmentTietojenkäsittelytieteen laitosfi
dc.contributor.schoolFaculty of Information and Natural Sciencesen
dc.contributor.schoolInformaatio- ja luonnontieteiden tiedekuntafi
dc.date.accessioned2011-11-28T13:19:22Z
dc.date.available2011-11-28T13:19:22Z
dc.date.issued2008
dc.description.abstractSeveral data analysis tools such as (kernel) canonical correlation analysis and various multi-view learning methods require paired observations in two data sets. We study the problem of inferring such pairing for data sets with no known one-to-one pairing. The pairing is found by an iterative algorithm that alternates between searching for feature representations that reveal statistical dependencies between the data sets, and finding the best pairs for the samples. The method is applied on pairing probe sets of two different microarray platforms.en
dc.format.extentv, 8
dc.format.mimetypeapplication/pdf
dc.identifier.isbn978-951-22-9596-8
dc.identifier.issn1797-5042
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/881
dc.identifier.urnurn:nbn:fi:tkk-012319
dc.language.isoenen
dc.publisherHelsinki University of Technologyen
dc.publisherTeknillinen korkeakoulufi
dc.relation.ispartofseriesTKK reports in information and computer scienceen
dc.relation.ispartofseries8en
dc.subject.keywordcanonical correlationen
dc.subject.keywordco-occurrence dataen
dc.subject.keyworddependencyen
dc.subject.keywordmulti-view learningen
dc.subject.otherComputer scienceen
dc.titleUsing dependencies to pair samples for multi-view learningen
dc.typeD4 Julkaistu kehittämis- tai tutkimusraportti taikka -selvitysfi
dc.type.dcmitypetexten
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