The Search of Causal Orderings: A Short Cut for Learning Belief Networks-Reference-Cited by-同舟云学术

The Search of Causal Orderings: A Short Cut for Learning Belief Networks

Published:2001 Issue: Volume: Page:216-227
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Acid Silvia,de Campos Luis M.,Huete Juan F.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-44652-4_20

Reference18 articles.

1. S. Acid and L.M. de Campos. An algorithm for finding minimum d-separating sets in belief networks. In Proceedings of the Conference on Uncertainty in Artificial Intelligence, E. Horvitz, F. Jensen (Eds.), pages 3–10 Morgan and Kaufmann, 1996.

2. S. Acid and L.M. de Campos. Benedict: An algorithm for learning probabilistic belief netwoks. In Proceedings of Information Processing and Management of Uncertainty in Knowledge-Based Systems, pages 979–984, 1996.

3. S. Acid and L.M. de Campos. An hybrid methodology for learning belief networks: Benedict. To appear in International Journal of Approximate Reasoning.

4. N. Ansari and E. Hou. Computational Intelligence for Optimization. Kluwer Academic Publishers, 1997.

5. I. Beinlich, H. Seurmondt, R. Chavez, and G. Cooper. The alarm monitoring system: a case study with two probabilistic inference techniques for belief networks. In Proceedings of the Second European Conference on Artificial Intelligence in Medicine, pages 247–256, 1989.

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A New Variable Ordering Method for the K2 Algorithm;Artificial Intelligence and Applied Mathematics in Engineering Problems;2020

2. Learning Bayesian networks: approaches and issues;The Knowledge Engineering Review;2011-05-12

3. Ant colony optimization for learning Bayesian networks;International Journal of Approximate Reasoning;2002-11