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Issue No.08 - August (1997 vol.19)
pp: 916-920
<p><b>Abstract</b>—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.</p>
Bayesian belief networks, belief network approximation, model simplification, approximate probabilistic inference, information theory.
Robert A van Engelen, "Approximating Bayesian Belief Networks by Arc Removal", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.19, no. 8, pp. 916-920, August 1997, doi:10.1109/34.608295
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