(Enter summary)
Abstract: Probabilistic inference algorithms for finding
the most probable explanation, the maximum
aposteriori hypothesis, and the maximum
expected utility and for updating belief
are reformulated as an elimination--type algorithm
called bucket elimination. This emphasizes
the principle common to many of
the algorithms appearing in that literature
and clarifies their relationship to nonserial
dynamic programming algorithms. We also
present a general way of combining conditioning
and... (Update)
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BibTeX entry: (Update)
Dechter, R. (1996). Bucket elimination: A unifying framework for probabilistic inference, in E. Horvits and F. Jensen (ed.), Proc. Twelthth Conf. on Uncertainty in Artificial Intelligence, Portland, Oregon, pp. 211--219. http://citeseer.ist.psu.edu/dechter96bucket.html More
@inproceedings{ dechterdechterbucket,
author = "Rina Dechter",
title = "Bucket elimination: {A} unifying framework for probabilistic inference",
pages = "211--219",
url = "citeseer.ist.psu.edu/dechter96bucket.html" }
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