Learning bayesian networks in semi-deterministic systems

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4013 LNAI, Issue , 2006, Pages 230-241

  Luo, Wei ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SCIENCE; CONSTRAINT THEORY; IMPROVEMENT; INTEGRATED CIRCUITS;

CONSTRAINT-BASED (PEARL-STYLE) SYSTEMS; NONDETERMINISTIC BAYESIAN NETWORKS; PEARL'S IC ALGORITHM; SEMI-DETERMINISTIC SYSTEMS;

LEARNING SYSTEMS;

EID: 33746065283     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11766247_20     Document Type: Conference Paper

References (18)

1. R. Agrawal and R. Srikant. Fast algorithms for mining association rules in large databases. In Proc International Conference on Very Large Databases, pages 478-499, Santiage, Chile, 1994. Morgan Kaufmann, Los Altos, CA.
2. P. A. Flach and N. Lachiche. Confirmation-guided discovery of first-order rules with tertius. Machine Learning, 42:61-95, 1999.
3. H.J. Hamilton and K. Karimi. The timers ii algorithm for the discovery of causality. In Proceedings of 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2005), pages 744-750, Hanoi, Vietnam, May 2005.
4. K. Karimi. Discovery of Causality and Acausality from Temporal Sequential Data. PhD thesis, University of Regina, 2005.
5. K. Karimi and H.J. Hamilton. Distinguishing causal and acausal temporal relations. In Proceedings of the Seventh Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'2003), pages 234-240, Seoul, South Korea, April/May 2003.
6. K. Karimi and Howard J. Hamilton. Discovering temporal/causal rules: A comparison of methods. In Canadian Conference on AI, pages 175-189, 2003.
7. J. L. Mackie. Causes and conditions. American Philosophical Quarterly, 2:245-264, 1966.
8. J. L. Mackie. The cement of the universe: a study of causation. Oxford: Clarendon Press, 1974.
9. K. P. Murphy. The bayes net toolbox for matlab. In Computing Science and Statistics, volume 33, pages 1-20, 2001.
10. J. Pearl. Probabilistic Reasoning in Intelligent Systems. Morgan Kauffmann, San Mateo, CA, 1988.
11. J. Pearl. Causality: Models, Reasoning, and Inference. Cambridge university press, 2000.
12. CMU Philosophy. Tetrad project. url: http://www.phil.cmu.edu/projects/ tetrad/.
13. S. J. Russell. Analogical and Inductive Reasoning. PhD thesis, Stanford University, 1986.
14. R. Scheines, P. Spirtes, C. Glymour, C. Meek, and T. Richardson. TETRAD 3:Tools for Causal Modeling - User's Manual. CMU Philosophy, 1996.
15. P. Spirtes, C. Glymour, and R. Scheines. Causation, prediction, and search. MIT Press, 2000.
16. J. D. Ullman. Principles of database systems. 2. Computer Science Press, 1982.
17. T. S. Verma and J. Pearl. Equivalence and synthesis of causal models. In Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence, pages 220-227, Mountain View, CA, 1990.
18. I. H. Witten and E. Frank. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, 2 edition, 2005.