Statistical Approaches to Learning Spring 1999 15-889 and 36-835

Professor Stephen Fienberg, Professor Tom Mitchell Dept of Statistics, Center for Automated Learning and Discovery Carnegie Mellon University

Class lectures: Mondays 1:30-3:20, Doherty 1209

Instructors:

Stephen Fienberg , Baker Hall 229B, x8-2723, Stephen.Fienberg@cmu.edu

Tom Mitchell, Wean Hall 5309, x8-2611, Tom.Mitchell@cmu.edu

Software: Downloadable Netica package for Bayes nets from Norsys.

Useful textbooks (optional):

Tools for Statistical Inference, M. Tanner, Springer Series in Statistics, 1996.
Machine Learning, T. Mitchell, McGraw Hill, 1997 (on reserve for our course in the E&S library).

Readings:

Combining Labeled and Unlabeled Data with Co-Training .
Avrim Blum and Tom Mitchell. Proceedings of the 11th Annual Conference on Computational Learning Theory (COLT-98).
A Tutorial on Learning with Bayesian Networks,
D. Heckerman, Microsoft Research Tech Report MSR-TR-95-06, 1996.
Learning Dynamic Bayesian Networks
Z. Ghahramani, In C.L. Giles and M. Gori (eds.), Adaptive Processing of Sequences and Data Structures . Lecture Notes in Artificial Intelligence, 168-197. Berlin: Springer-Verlag.
Friedman, J. H., Hastie, T. and Tibshirani, R. "Additive Logistic Regression: a Statistical View of Boosting." (Aug. 1998)
list of MCMC papers

Homeworks: