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.
@article{arxiv.1301.6742,
title = {Multiplicative Factorization of Noisy-Max},
author = {Masami Takikawa and Bruce D'Ambrosio},
journal= {arXiv preprint arXiv:1301.6742},
year = {2013}
}
Comments
Appears in Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI1999)