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Independence of causal influence and clique tree propagation

✍ Scribed by Nevin Lianwen Zhang; Li Yan


Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
716 KB
Volume
19
Category
Article
ISSN
0888-613X

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✦ Synopsis


This paper explores the role of independence of causal influence (ICI) in Bayesian network inference. ICI allows one to factorize a conditional probability table into smaller pieces. We describe a method for exploiting the factorization in clique tree propagation (CTP) -the state-of-the-art exact inference algorithm for Bayesian networks (BNS). We also present empirical results showing that the resulting algorithm is significantly more efficient than the combination of CTP and previous techniques for exploiting ICI.


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