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Approximating Probability Density Functions with Mixtures of Truncated Exponentials

dc.contributor.authorCobb, Barry R.
dc.contributor.authorShenoy, Prakash P.
dc.contributor.authorRumi, Rafael
dc.date.accessioned2005-11-02T22:37:11Z
dc.date.available2005-11-02T22:37:11Z
dc.date.issued2004-07
dc.identifier.citationCobb, B. R., P. P. Shenoy, and R. Rumi, "Approximating Probability Density Functions with Mixtures of Truncated Exponentials," Proceedings of the Tenth Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU-04), pp. 429--436, 2004, Perugia, Italy
dc.identifier.urihttp://hdl.handle.net/1808/761
dc.description.abstractMixtures of truncated exponentials (MTE) potentials are an alternative to discretization for approximating probability density functions (PDF’s). This paper presents MTE potentials that approximate standard PDF’s and applications of these potentials for solving inference problems in hybrid Bayesian networks.
dc.format.extent385164 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectHybrid Bayesian networks
dc.subjectMixtures of truncated exponentials
dc.subjectShenoy-Shafer architecture
dc.titleApproximating Probability Density Functions with Mixtures of Truncated Exponentials
dc.typeBook chapter
kusw.oastatusna
dc.identifier.orcidhttps://orcid.org/0000-0002-8425-896X
kusw.oapolicyThis item does not meet KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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