Uncertainty in Artificial Intelligence
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Multiplicative Factorization of Noisy-Max
Masami Takikawa, Bruce D'Ambrosio
Abstract:
The noisy-or and its generalization noisy-max have been utilized to reduce the complexity of knowledge acquisition. In this paper, we present a new representation of noisy-max that allows for efficient inference in general Bayesian networks. Empirical studies show that our method is capable of computing queries in well-known large medical networks, QMR-DT and CPCS, for which no previous exact inference method has been shown to perform well.
Keywords:
Pages: 622-630
PS Link:
PDF Link: /papers/99/p622-takikawa.pdf
BibTex:
@INPROCEEDINGS{Takikawa99,
AUTHOR = "Masami Takikawa and Bruce D'Ambrosio",
TITLE = "Multiplicative Factorization of Noisy-Max",
BOOKTITLE = "Proceedings of the Fifteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-99)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1999",
PAGES = "622--630"
}


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