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dc.contributor.authorLangseth, Helge
dc.contributor.authorNielsen, Thomas D.
dc.contributor.authorRumí, Rafael
dc.contributor.authorSalmerón Cerdán, Antonio
dc.date.accessioned2017-07-05T08:37:35Z
dc.date.available2017-07-05T08:37:35Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/10835/4886
dc.description.abstractIn this paper we propose a framework, called mixtures of truncated basis functions (MoTBFs), for representing general hybrid Bayesian networks. The proposed framework generalizes both the mixture of truncated exponentials (MTEs) framework and the mixture of polynomials (MoPs) framework. Similar to MTEs and MoPs, MoTBFs are defined so that the potentials are closed under combination and marginalization, which ensures that inference in MoTBF networks can be performed efficiently using the Shafer-Shenoy architecture. Based on a generalized Fourier series approximation, we devise a method for efficiently pproximating an arbitrary density function using the MoTBF framework. The translation method is more flexible than existing MTE or MoP-based methods, and it supports an online/anytime tradeoff between the accuracy and the complexity of the approximation. Experimental results show that the approximations obtained are either comparable or significantly better than the approximations obtained using existing methods.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.subjectHybrid Bayesian networkses_ES
dc.subjectApproximationses_ES
dc.subjectMixtures of truncated basis functionses_ES
dc.subjectMixtures of truncated exponentialses_ES
dc.subjectInferencees_ES
dc.titleMixtures of Truncated Basis Functionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doiDOI: 10.1016/j.ijar.2011.10.004


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