DocumentCode
2914415
Title
Some practical issues in inference in hybrid Bayesian networks with deterministic conditionals
Author
Shenoy, Prakash P. ; Rumí, Rafael ; Salmerón, Antonio
Author_Institution
Sch. of Bus., Univ. of Kansas, Lawrence, KS, USA
fYear
2011
fDate
22-24 Nov. 2011
Firstpage
605
Lastpage
610
Abstract
In this paper we analyze the use of hybrid Bayesian networks in domains that include deterministic conditionals for continuous variables. We show how exact inference can become infeasible even for small networks, due to the difficulty in handling functional relationships. We compare two strategies for carrying out the inference task, using mixtures of polynomials (MOPs) and mixtures of truncated exponentials (MTEs).
Keywords
belief networks; deterministic algorithms; inference mechanisms; polynomials; continuous variables; deterministic conditionals; functional relationship handling; hybrid Bayesian networks; inference task; mixtures-of-polynomials; mixtures-of-truncated exponentials; Approximation methods; Bayesian methods; Hypercubes; Intelligent systems; Polynomials; Random variables; Stochastic processes; deterministic conditionals; hybrid Bayesian networks; mixtures of polynomials; mixtures of truncated exponentials;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on
Conference_Location
Cordoba
ISSN
2164-7143
Print_ISBN
978-1-4577-1676-8
Type
conf
DOI
10.1109/ISDA.2011.6121722
Filename
6121722
Link To Document