Efficient computation for the noisy MAX
2003; Wiley; Volume: 18; Issue: 2 Linguagem: Inglês
10.1002/int.10080
ISSN1098-111X
AutoresFrancisco Javier Díez, Severino F. Galán,
Tópico(s)Network Packet Processing and Optimization
ResumoInternational Journal of Intelligent SystemsVolume 18, Issue 2 p. 165-177 Efficient computation for the noisy MAX Francisco J. Díez, Corresponding Author Francisco J. Díez [email protected] Department Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Senda del Rey, 9. 28430 Madrid, SpainDepartment Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Senda del Rey, 9. 28430 Madrid, SpainSearch for more papers by this authorSeverino F. Galán, Severino F. Galán Department Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Senda del Rey, 9. 28430 Madrid, SpainSearch for more papers by this author Francisco J. Díez, Corresponding Author Francisco J. Díez [email protected] Department Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Senda del Rey, 9. 28430 Madrid, SpainDepartment Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Senda del Rey, 9. 28430 Madrid, SpainSearch for more papers by this authorSeverino F. Galán, Severino F. Galán Department Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Senda del Rey, 9. 28430 Madrid, SpainSearch for more papers by this author First published: 17 January 2003 https://doi.org/10.1002/int.10080Citations: 36AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract Díez's algorithm for the noisy MAX is very efficient for polytrees, but when the network has loops, it has to be combined with local conditioning, a suboptimal propagation algorithm. Other algorithms, based on several factorizations of the conditional probability of the noisy MAX, are not as efficient for polytrees but can be combined with general propagation algorithms such as clustering or variable elimination, which are more efficient for networks with loops. In this article we propose a new factorization of the noisy MAX that amounts to Díez's algorithm in the case of polytrees and at the same time is more efficient than previous factorizations when combined with either variable elimination or clustering. © 2003 Wiley Periodicals, Inc. References 1 Díez FJ, Druzdzel M. Canonical probabilistic models for knowledge engineering. 2002. Technical Report IA-2002-01, Dept. Inteligencia Artificial, UNED, Madrid. 2 Díez FJ. Parameter adjustment in Bayes networks. The generalized noisy OR-gate. In: Proc 9th Conf on Uncertainty in Artificial Intelligence (UAI'93). Washington D.C., 1993. San Mateo, CA: Morgan Kaufmann; 1993. pp 99– 105. 3 Takikawa M, D'Ambriosio B. 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