Inference in credal networks through integer programming

Cassio Polpo De Campos; Fabio Gagliardi Cozman

Inference in credal networks through integer programming

Cassio Polpo De Campos, Fabio Gagliardi Cozman

Research output: Contribution to conference › Conference Paper

21 Scopus citations

Abstract

A credal network associates a directed acyclic graph with a collection of sets of probability measures; it offers a compact representation for sets of multivariate distributions. In this paper we present a new algorithm for inference in credal networks based on an integer programming reformulation. We are concerned with computation of lower/upper probabilities for a variable in a given credal network. Experiments reported in this paper indicate that this new algorithm has better performance than existing ones for some important classes of networks. Copyright © 2007 by SIPTA.

Original language	American English
Pages	145-154
Number of pages	10
State	Published - 1 Dec 2007
Externally published	Yes
Event	ISIPTA 2007 - Proceedings of the 5th International Symposium on Imprecise Probability: Theories and Applications - Duration: 1 Dec 2007 → …

Conference

Conference	ISIPTA 2007 - Proceedings of the 5th International Symposium on Imprecise Probability: Theories and Applications
Period	1/12/07 → …

Cite this

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title = "Inference in credal networks through integer programming",

abstract = "A credal network associates a directed acyclic graph with a collection of sets of probability measures; it offers a compact representation for sets of multivariate distributions. In this paper we present a new algorithm for inference in credal networks based on an integer programming reformulation. We are concerned with computation of lower/upper probabilities for a variable in a given credal network. Experiments reported in this paper indicate that this new algorithm has better performance than existing ones for some important classes of networks. Copyright {\textcopyright} 2007 by SIPTA.",

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AB - A credal network associates a directed acyclic graph with a collection of sets of probability measures; it offers a compact representation for sets of multivariate distributions. In this paper we present a new algorithm for inference in credal networks based on an integer programming reformulation. We are concerned with computation of lower/upper probabilities for a variable in a given credal network. Experiments reported in this paper indicate that this new algorithm has better performance than existing ones for some important classes of networks. Copyright © 2007 by SIPTA.

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ER -

Inference in credal networks through integer programming

Abstract

Conference

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