Inter-causal Independence and Heterogeneous Factorization

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.

Appears in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence (UAI1994)