Inter-causal Independence and Heterogeneous Factorization
Nevin Zhang, David Poole
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.
Keywords: Bayesian networks, inter-causal independence (definition, representation, inference).
PS Link: ftp://ftp.cs.ust.hk/pub/lzhang/uai94.Z
PDF Link: /papers/94/p606-zhang.pdf
AUTHOR = "Nevin Zhang
and David Poole",
TITLE = "Inter-causal Independence and Heterogeneous Factorization",
BOOKTITLE = "Proceedings of the Tenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-94)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1994",
PAGES = "606--614"