Inter-causal Independence and Heterogeneous Factorization

2013/02/27 by Zhang, Nevin Lianwen, Poole, David L
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences

paper · doi:10.48550/arxiv.1302.6855

Abstract

It is well known that conditional independence can be used to factorize a joint probability into a multiplication of conditional probabilities. This paper proposes a constructive definition of inter-causal independence, which can be used to further factorize a conditional probability. An inference algorithm is developed, which makes use of both conditional independence and inter-causal independence to reduce inference complexity in Bayesian networks.

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