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  1. Approximating MAPs for belief networks is NP-hard and other theorems.Ashraf M. Abdelbar & Sandra M. Hedetniemi - 1998 - Artificial Intelligence 102 (1):21-38.
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  • Fusion, propagation, and structuring in belief networks.Judea Pearl - 1986 - Artificial Intelligence 29 (3):241-288.
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  • An optimal approximation algorithm for Bayesian inference.Paul Dagum & Michael Luby - 1997 - Artificial Intelligence 93 (1-2):1-27.
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  • Finding MAPs for belief networks is NP-hard.Solomon Eyal Shimony - 1994 - Artificial Intelligence 68 (2):399-410.
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  • Approximating probabilistic inference in Bayesian belief networks is NP-hard.Paul Dagum & Michael Luby - 1993 - Artificial Intelligence 60 (1):141-153.
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  • The computational complexity of probabilistic inference using bayesian belief networks.Gregory F. Cooper - 1990 - Artificial Intelligence 42 (2-3):393-405.
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