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Support Vector Method for Novelty Detection

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dc.contributor.authorSchoelkopf, Bernhard
dc.contributor.authorWilliamson, Robert
dc.contributor.authorSmola, Alexander
dc.contributor.authorShawe-Taylor, John
dc.contributor.authorPlatt, John
dc.coverage.spatialColorado USA
dc.date.accessioned2015-12-13T23:22:02Z
dc.date.available2015-12-13T23:22:02Z
dc.date.createdNovember 29 1999
dc.date.issued2000
dc.date.updated2015-12-12T09:09:42Z
dc.identifier.isbn1049-5258
dc.identifier.urihttp://hdl.handle.net/1885/91255
dc.publisherMIT Press
dc.relation.ispartofseriesConference on Advances in Neural Information Processing Systems (NIPS 1999)
dc.sourceAdvances in Neural Information Processing Systems: Proceedings of the 1999 Conference
dc.titleSupport Vector Method for Novelty Detection
dc.typeConference paper
local.bibliographicCitation.lastpage588
local.bibliographicCitation.startpage582
local.contributor.affiliationSchoelkopf, Bernhard, Max Planck Institute for Biological Cybernetics
local.contributor.affiliationWilliamson, Robert, College of Engineering and Computer Science, ANU
local.contributor.affiliationSmola, Alexander, College of Engineering and Computer Science, ANU
local.contributor.affiliationShawe-Taylor, John, University of London
local.contributor.affiliationPlatt, John, Microsoft Research Ltd.
local.contributor.authoruidWilliamson, Robert, u9000163
local.contributor.authoruidSmola, Alexander, u4039398
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.ariespublicationMigratedxPub21943
local.type.statusPublished Version

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