ML Anthology

Intercausal Independence and Heterogeneous Factorization

Nevin Lianwen Zhang, David L. Poole
UAI 1994 pp. 606-614
doi:10.1016/B978-1-55860-332-5.50082-1 /uai/1994/zhang1994uai-intercausal/

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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Text

Zhang and Poole. "Intercausal Independence and Heterogeneous Factorization." Conference on Uncertainty in Artificial Intelligence, 1994. doi:10.1016/B978-1-55860-332-5.50082-1

Markdown

[Zhang and Poole. "Intercausal Independence and Heterogeneous Factorization." Conference on Uncertainty in Artificial Intelligence, 1994.](https://mlanthology.org/uai/1994/zhang1994uai-intercausal/) doi:10.1016/B978-1-55860-332-5.50082-1

BibTeX

@inproceedings{zhang1994uai-intercausal,
  title     = {{Intercausal Independence and Heterogeneous Factorization}},
  author    = {Zhang, Nevin Lianwen and Poole, David L.},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {1994},
  pages     = {606-614},
  doi       = {10.1016/B978-1-55860-332-5.50082-1},
  url       = {https://mlanthology.org/uai/1994/zhang1994uai-intercausal/}
}