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dc.contributor.authorBooth, Richard
dc.contributor.authorChevaleyre, Yann
dc.contributor.authorLang, Jérôme
dc.contributor.authorMengin, Jérôme
HAL ID: 184956
dc.contributor.authorSombattheera, Chattrakul
dc.date.accessioned2010-12-17T10:48:54Z
dc.date.available2010-12-17T10:48:54Z
dc.date.issued2009
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/5339
dc.language.isoenen
dc.subjectpreferences
dc.subjectgraphical representation
dc.subjectComplexity
dc.subject.ddc006.3en
dc.titleLearning various classes of models of lexicographic orderings
dc.typeCommunication / Conférence
dc.description.abstractenWe consider the problem of learning a user’s ordinal preferences onmultiattribute domains, assuming that the user’s preferences may be modelled asa kind of lexicographic ordering. We introduce a general graphical representationcalled LP-structures which captures various natural classes of such ordering inwhich both the order of importance between attributes and the local preferencesover each attributemay or may not be conditional on the values of other attributes.For each class we determine the Vapnik-Chernovenkis dimension, the communication complexity of learning preferences, and the complexity of identifying amodel in the class consistent with some given user-provided examples.
dc.description.sponsorshipprivateouien
dc.subject.ddclabelIntelligence artificielleen
dc.relation.conftitlePreference Learning (PL-09) ECML/PKDD-09 Workshop
dc.relation.confcityBled
dc.relation.confcountrySLOVENIA
dc.description.ssrncandidatenon
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
dc.date.updated2017-09-29T16:51:37Z


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