Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions

Helge Langseth; Thomas Dyhre Nielsen; Rafael Rumí; Antonio Salmerón

Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions

Helge Langseth, Thomas Dyhre Nielsen, Rafael Rumí, Antonio Salmerón

Institut for Datalogi

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Bidrag til bog/antologi › Forskning › peer review

13 Citationer (Scopus)

238 Downloads (Pure)

Abstract

In this paper we study the problem of exact inference in hybrid Bayesian networks using mixtures of truncated basis functions (MoTBFs). We propose a structure for handling probability potentials called Sum-Product factorized potentials, and show how these potentials facilitate efficient inference based on i) properties of the MoTBFs and ii) ideas similar to the ones underlying Lazy propagation (postponing operations and keeping factorized representations of the potentials). We report on preliminary experiments demon- strating the efficiency of the proposed method in comparison with existing algorithms.

Originalsprog	Engelsk
Titel	Proceedings of the Sixth European Workshop on Probabilistic Graphical Models
Redaktører	Andrés Cano, Manuel Gómez-Olmedo, Thomas Dyhre Nielsen
Antal sider	8
Forlag	DECSAI, University of Granada
Publikationsdato	2012
Sider	171-178
ISBN (Trykt)	978-84-15536-57-4
Status	Udgivet - 2012
Begivenhed	The 6th European Workshop on Probabilistic Graphical Models - Granada, Spanien Varighed: 19 sep. 2012 → 21 sep. 2012

Konference

Konference	The 6th European Workshop on Probabilistic Graphical Models
Land/Område	Spanien
By	Granada
Periode	19/09/2012 → 21/09/2012

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Langseth etal 12bIndsendt manuskript, 123 KB

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title = "Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions",

abstract = "In this paper we study the problem of exact inference in hybrid Bayesian networks using mixtures of truncated basis functions (MoTBFs). We propose a structure for handling probability potentials called Sum-Product factorized potentials, and show how these potentials facilitate efficient inference based on i) properties of the MoTBFs and ii) ideas similar to the ones underlying Lazy propagation (postponing operations and keeping factorized representations of the potentials). We report on preliminary experiments demon- strating the efficiency of the proposed method in comparison with existing algorithms.",

author = "Helge Langseth and Nielsen, {Thomas Dyhre} and Rafael Rum{\'i} and Antonio Salmer{\'o}n",

year = "2012",

language = "English",

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pages = "171--178",

editor = "Andr{\'e}s Cano and Manuel G{\'o}mez-Olmedo and Nielsen, {Thomas Dyhre}",

booktitle = "Proceedings of the Sixth European Workshop on Probabilistic Graphical Models",

publisher = "DECSAI, University of Granada",

note = "The 6th European Workshop on Probabilistic Graphical Models ; Conference date: 19-09-2012 Through 21-09-2012",

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Langseth, H, Nielsen, TD, Rumí, R & Salmerón, A 2012, Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions. i A Cano, M Gómez-Olmedo & TD Nielsen (red), Proceedings of the Sixth European Workshop on Probabilistic Graphical Models. DECSAI, University of Granada, s. 171-178, The 6th European Workshop on Probabilistic Graphical Models, Granada, Spanien, 19/09/2012. <http://leo.ugr.es/pgm2012/>

Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions. / Langseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael et al.
Proceedings of the Sixth European Workshop on Probabilistic Graphical Models. red. / Andrés Cano; Manuel Gómez-Olmedo; Thomas Dyhre Nielsen. DECSAI, University of Granada, 2012. s. 171-178.

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Bidrag til bog/antologi › Forskning › peer review

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Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions

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