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Approximating Bayesian Belief Networks by Arc Removal
August 1997 (vol. 19 no. 8)
pp. 916-920

Abstract—I propose a general framework for approximating Bayesian belief networks through model simplification by arc removal. Given an upper bound on the absolute error allowed on the prior and posterior probability distributions of the approximated network, a subset of arcs is removed, thereby speeding up probabilistic inference.

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Index Terms:
Bayesian belief networks, belief network approximation, model simplification, approximate probabilistic inference, information theory.
Citation:
Robert A van Engelen, "Approximating Bayesian Belief Networks by Arc Removal," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 8, pp. 916-920, Aug. 1997, doi:10.1109/34.608295
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