Uncertainty in Artificial Intelligence
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A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks
Dan Geiger, David Heckerman
Abstract:
We provide a new characterization of the Dirichlet distribution. This characterization implies that under assumptions made by several previous authors for learning belief networks, a Dirichlet prior on the parameters is inevitable.
Keywords:
Pages: 196-207
PS Link: http://www.research.microsoft.com/research/dtg/heckerma/TR-94-16.htm
PDF Link: /papers/95/p196-geiger.pdf
BibTex:
@INPROCEEDINGS{Geiger95,
AUTHOR = "Dan Geiger and David Heckerman",
TITLE = "A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks",
BOOKTITLE = "Proceedings of the Eleventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-95)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1995",
PAGES = "196--207"
}


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