Advances in Probabilistic Reasoning
Abstract
This paper discuses multiple Bayesian networks representation paradigms for encoding asymmetric independence assertions. We offer three contributions: (1) an inference mechanism that makes explicit use of asymmetric independence to speed up computations, (2) a simplified definition of similarity networks and extensions of their theory, and (3) a generalized representation scheme that encodes more types of asymmetric independence assertions than do similarity networks.
Cite
Text
Geiger and Heckerman. "Advances in Probabilistic Reasoning." Conference on Uncertainty in Artificial Intelligence, 1991.Markdown
[Geiger and Heckerman. "Advances in Probabilistic Reasoning." Conference on Uncertainty in Artificial Intelligence, 1991.](https://mlanthology.org/uai/1991/geiger1991uai-advances/)BibTeX
@inproceedings{geiger1991uai-advances,
title = {{Advances in Probabilistic Reasoning}},
author = {Geiger, Dan and Heckerman, David},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1991},
url = {https://mlanthology.org/uai/1991/geiger1991uai-advances/}
}