John Burge’s Recommended Reading List

Shrinkage Papers

Improving text classification by shrinkage in a hierarchy of classes. Andrew McCallum, Ronald Rosenfeld, Tom Mitchell, and Andrew Ng. ICML-98, pages 359--367, 1998.
Information Extraction with HMMs and Shrinkage. Freitag, D. and A. McCallum. Proceedings of the Sixteenth National Conference on Artificial Intelligence: Workshop on Machine Learning for Information Extraction. Orlando, FL, pp. 31—36, 1999
Relational Markov models and their application to adaptive Web navigation. C. Anderson, P. Domingos, and D. Weld. Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 143--152, Edmonton, Canada, 2002.

Bayesian Network Papers

Structure Search

· On Inclusion-Driven Learning of Bayesian Networks. Robert Castelo, Tomás Kocka. Journal of Machine Learning, 4(Sep):527-574, 2003.

· Optimal Reinsertion: A new search operator for accelerated and more accurate Bayesian network structure learning. Andrew Moore and Weng-Keen Wong. Proceedings of the 20th International Conference on Machine Learning, 2003

Relational Learning Papers

· Approximate Inference for First-Order Probabilistic Languages. H. Pasula and S. Russell. In IJCAI-01, 2001.

· Bayesian Logic Programs. Kersting, K. and L. De Raedt. In Work-in- 38 Progress Reports of the Tenth International Conference on Inductive Logic Programming (ILP -2000), 2000. http://SunSITE.Informatik.RWTH-Aachen.DE/ Publications/CEUR-WS/Vol-35/.

· Learning Probabilistic Relational Models. L. Getoor, N. Friedman, D. Koller, and A. Pfeffer. In IJCAI '99. 1999.

· Learning Stochastic Logic Programs. S. Muggleton. In Proceedings of the AAAI2000 Workshop on Learning Statistical Models from Relational Data. AAAI, 2000.

· Parameter estimation in stochastic logic programs. Cussens, J. In press. Dekhtyar, A. and Subrahmanian, Hybrid probabilistic programs. Journal of Logic Programming 43, 3, 187-250, 2000.

· Probabilistic Horn abduction and Bayesian networks. D. Poole. Artificial Intelligence, 64(1):81--129, November 1993.

· Probabilistic Logic Programming. R. T. Ng and V. S. Subrahmanian. Information and Computation, 101, 2, pps 150--201, 1993.

· Probabilistic Logic Programming and Bayesian Networks. L. Ngo and P. Haddawy. In Proceedings of the 1995 Asian Computing Science Conference, pages 286--300, 1995.

· Relational Bayesian Networks. M. Jaeger. In Proceedings of the 13th Conference on Uncertainty in Artificial Intelligence, pages 266--273. Morgan Kaufmann, 1997.

· Tracking Many Objects with Many Sensors. H. Pasula, S. Russell, M. Ostland, and Y. Ritov. In Int. Joint Conf. on Artificial Intelligence (IJCAI), Stockholm, 1999.

· Using First-Order Probability Logic for the Construction of Bayesian Networks. F. Bacchus. In Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence, pages 219--226, July 1993.

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