Uncertainty in Artificial Intelligence
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A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability Distributions
Vasilica Lepar, Prakash Shenoy
Abstract:
In the last decade, several architectures have been proposed for exact computation of marginals using local computation. In this paper, we compare three architectures --Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer-- from the perspective of graphical structure for message propagation, message-passing scheme, computational efficiency, and storage efficiency.
Keywords: architectures for probabilistic inference
Pages: 328-337
PS Link:
PDF Link: /papers/98/p328-lepar.pdf
BibTex:
@INPROCEEDINGS{Lepar98,
AUTHOR = "Vasilica Lepar and Prakash Shenoy",
TITLE = "A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability Distributions",
BOOKTITLE = "Proceedings of the Fourteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-98)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1998",
PAGES = "328--337"
}


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