Learning Changing Concepts by Exploiting the Structure of Change

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dc.contributor.authorBartlett, Peter
dc.contributor.authorBen-David, Shai
dc.contributor.authorKulkarni, Shrinivas R
dc.date.accessioned2015-12-13T23:18:50Z
dc.date.issued2000
dc.date.updated2015-12-12T08:58:24Z
dc.description.abstractThis paper examines learning problems in which the target function is allowed to change. The learner sees a sequence of random examples, labelled according to a sequence of functions, and must provide an accurate estimate of the target function sequence.
dc.identifier.issn0885-6125
dc.identifier.urihttp://hdl.handle.net/1885/90370
dc.publisherKluwer Academic Publishers
dc.sourceMachine Learning
dc.subjectKeywords: Algorithms; Computational complexity; Functions; Graph theory; Parameter estimation; Computational learning theory; Concept drift; Learning systems
dc.titleLearning Changing Concepts by Exploiting the Structure of Change
dc.typeJournal article
local.bibliographicCitation.issue2
local.bibliographicCitation.lastpage174
local.bibliographicCitation.startpage153
local.contributor.affiliationBartlett, Peter, College of Engineering and Computer Science, ANU
local.contributor.affiliationBen-David, Shai, Technion University
local.contributor.affiliationKulkarni, Shrinivas R, California Institute of Technology
local.contributor.authoruidBartlett, Peter, u9301805
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080105 - Expert Systems
local.identifier.ariespublicationMigratedxPub20711
local.identifier.citationvolume41
local.identifier.doi10.1023/A:1007604202679
local.identifier.scopusID2-s2.0-0034320912
local.type.statusPublished Version

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