Active learning of causal networks with intervention experiments and optimal designs

Journal of Machine Learning Research

Volumn 9, Issue , 2008, Pages 2523-2547

  He, Yang Bo ^a   Geng, Zhi ^a  

^a PEKING UNIVERSITY   (China)

Author keywords

Active learning; Causal networks; Directed acyclic graphs; Intervention; Markov equivalence class; Optimal design; Structural learning

Indexed keywords

DATA STRUCTURES; DESIGN; EDUCATION; EXPERIMENTS; OPTIMAL SYSTEMS; OPTIMIZATION; SET THEORY;

ACTIVE LEARNING; CAUSAL NETWORKS; DIRECTED ACYCLIC GRAPHS; INTERVENTION; MARKOV EQUIVALENCE CLASS; OPTIMAL DESIGN; STRUCTURAL LEARNING;

EQUIVALENCE CLASSES;

EID: 57249084023     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article

References (23)

1. C. Aliferis, I. Tsamardinos, A. Statnikov and L. Brown. Causal explorer: A probabilistic network learning toolkkit for biomedical discovery. In International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, pages 371-376, 2003.
2. S. A. Andersson, D. Madigan and M. D. Perlman. A characterization of markov equivalence classes for acyclic digraphs. Annals of Statistics, 25:505-541, 1997.
3. R. Castelo and M. D. Perlman. Learning Essential graph Markov models from data. In Proceedings 1st European Workshop on Probabilistic Graphical Models, pages 17-24, 2002.
4. G. F. Cooper and C. Yoo. Causal discovery from a mixture of experimental and observational data. In Proceedings of the Conference on Uncertainty in Artificial Intelligence, pages 116-125, 1999.
5. N. Friedman. Inferring cellular networks using probabilistic graphical models. Science, 303(5659):799-805, 2004.
6. Y. He, Z. Geng and X. Liang. Learning causal structures based on Markov equivalence class. In ALT, Lecture Notes in Artificial Intelligence 3734, pages 92-106, 2005.
7. D. Heckerman, D. Geiger and D. M. Chickering. Learning Bayesian networks: The Combination of knowledge and statistical data. Machine Learning, 20:197-243, 1995.
8. D. Heckerman. A Bayesian approach to causal discovery. Data Mining and Knowledge Discovery, 1(1):79-119, 1997.
9. R. Jansen, H. Y. Yu and D. Greenbaum. A Bayesian networks approach for predicting proteinprotein interactions from genomic data. Science, 302(5644):449-453, 2003.
10. S. L. Lauritzen. Graphical Models. Oxford Univ. Press. 1996.
11. S. L. Lauritzen, T. S. Richardson. Chain graph models and their casual interpretations. Journal of the Royal Statistical society series B-statistical methodology,64:321-348, Part 3, 2002.
12. M. Kalisch, P. Buhlmann. Estimating high-dimensional directed acyclic graphs with the PC-algorithm Journal of Machine Learning Research 8, 613-636, 2007.
13. K. P. Murphy. Active Learning of Causal Bayes Net Structure, Technical Report, Department of Computer Science, University of California Berkeley, 2001.
14. J. Pearl. Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann, 1988.
15. J. Pearl. Graphical models, causality and intervention. Statist. Sci., 8:266-269, 1993.
16. J. Pearl. Causal inference from indirect experiments. Artifcal Intelligence in Medicine, 7:561-582, 1995.
17. J. Pearl. Causality: Models, Reasoning, and Inference. Cambridge University Press, 2000.
18. P. Spirtes, C. Glymour, R. Scheines. Causation, Prediction, and Search. MIT Press, Cambridge, MA, second edition, 2000.
19. J. Tian and J. Pearl. Causal Discovery from Changes. In Proceedings of the Conference on Uncertainty in Artificial Intelligence, pages 512-521, 2001a.
20. J. Tian and J. Pearl. Causal Discovery from Changes: a Bayesian Approach, UCLA Cognitive Systems Laboratory, Technical Report (R-285), 2001b.
21. S. Tong and D. Koller. Active learning for structure in bayesian networks. In International Joint Conference on Artificial Intelligence, pages 863-869, 2001.
22. T. Verma and J. Pearl. Equivalence and synthesis of causal models. In Proceedings of the Conference on Uncertainty in Artificial Intelligence, pages 220-227, 1990.
23. J. Whittaker. Graphical Models in Applied Multivariate Statistics. Wiley, New York. 1990.