Multiplicative Factorization of Noisy-Max
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.
Cite
Text
Takikawa and D'Ambrosio. "Multiplicative Factorization of Noisy-Max." Conference on Uncertainty in Artificial Intelligence, 1999.Markdown
[Takikawa and D'Ambrosio. "Multiplicative Factorization of Noisy-Max." Conference on Uncertainty in Artificial Intelligence, 1999.](https://mlanthology.org/uai/1999/takikawa1999uai-multiplicative/)BibTeX
@inproceedings{takikawa1999uai-multiplicative,
title = {{Multiplicative Factorization of Noisy-Max}},
author = {Takikawa, Masami and D'Ambrosio, Bruce},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1999},
pages = {622-630},
url = {https://mlanthology.org/uai/1999/takikawa1999uai-multiplicative/}
}