Factorization of Sparse Bayesian Networks

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Studies in Computational Intelligence 199:275-285 (2009)
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Abstract

This paper shows how an efficient and parallel algorithm for inference in Bayesian Networks (BNs) can be built and implemented combining sparse matrix factorization methods with variable elimination algorithms for BNs. This entails a complete separation between a first symbolic phase, and a second numerical phase.

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Julio Michael Stern
University of São Paulo

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