Uncertainty in Artificial Intelligence
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A factorization criterion for acyclic directed mixed graphs
Thomas Richardson
Abstract:
Acyclic directed mixed graphs, also known as semi-Markov models represent the conditional independence structure induced on an observed margin by a DAG model with latent variables. In this paper we present a factorization criterion for these models that is equivalent to the global Markov property given by (the natural extension of) d-separation.
Keywords: null
Pages: 462-470
PS Link:
PDF Link: /papers/09/p462-richardson.pdf
BibTex:
@INPROCEEDINGS{Richardson09,
AUTHOR = "Thomas Richardson ",
TITLE = "A factorization criterion for acyclic directed mixed graphs",
BOOKTITLE = "Proceedings of the Twenty-Fifth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-09)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "2009",
PAGES = "462--470"
}


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