Show simple item record

dc.contributor.authorCano, Andrés
dc.contributor.authorGómez Olmedo, Manuel
dc.contributor.authorPérez-Ariza, Cora B.
dc.contributor.authorSalmerón Cerdán, Antonio
dc.date.accessioned2017-07-05T08:37:24Z
dc.date.available2017-07-05T08:37:24Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/10835/4885
dc.description.abstractWe present an efficient procedure for factorising probabilistic potentials represented as probability trees. This new procedure is able to detect some regularities that cannot be captured by existing methods. In cases where an exact decomposition is not achievable, we propose a heuristic way to carry out approximate factorisations guided by a parameter called factorisation degree, which is fast to compute. We show how this parameter can be used to control the tradeoff between complexity and accuracy in approximate inference algorithms for Bayesian networks.es_ES
dc.language.isoenes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourcePreprint of an article submitted for consideration in International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems © 2012 [copyright World Scientific Publishing Company] http://www.worldscientific.com/worldscinet/ijufkses_ES
dc.subjectBayesian netwoorkses_ES
dc.subjectProbability treeses_ES
dc.subjectFactorisationes_ES
dc.subjectProbabilistic inferencees_ES
dc.titleFast factorisation of probabilistic potentials and its application to approximate inference in Bayesian networkses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttp://www.worldscientific.com/doi/pdf/10.1142/S0218488512500110es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doihttps://doi.org/10.1142/S0218488512500110


Files in this item

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional