On the Role of Context-Specific Independence in Probabilistic Inference
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence. Uncertainty and Probabilistic Reasoning. Pages 1288-1292.
Abstract
Context-specific independence (CSI) refers to conditional independencies that are true only in specific contexts. It has been found useful in various inference algorithms for Bayesian networks. This paper studies the role of CSI in general. We provide a characterization of the computational leverages offered by CSI without referring to particular inference algorithms. We identify the issues that need to be addressed in order to exploit the leverages and show how those issues can be addressed. We also provide empirical evidence that demonstrates the usefulness of CSI.
@inproceedings{ijcai1999p183,
title = {On the Role of Context-Specific Independence in Probabilistic Inference},
author = {Zhang, Nevin Lianwen and Poole, David},
booktitle = {Proceedings of the Sixteenth International Joint Conference on
Artificial Intelligence, {IJCAI-99}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Thomas Dean},
pages = {1288--1292},
year = {1999},
note = {Uncertainty and Probabilistic Reasoning},
url = {https://ijcai.org/proceedings/1999/183},
}
TY - CPAPER TI - On the Role of Context-Specific Independence in Probabilistic Inference AU - Zhang, Nevin Lianwen AU - Poole, David T2 - Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI-99 PB - International Joint Conferences on Artificial Intelligence PY - 1999 SP - 1288 EP - 1292 UR - https://ijcai.org/proceedings/1999/183 ER -Copied
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