Statistical Approaches to Learning
Spring 1999
15889 and 36835
Professor Stephen Fienberg, Professor Tom Mitchell
Dept of Statistics, Center for Automated Learning and
Discovery
Carnegie Mellon University
Class lectures: Mondays 1:303:20, Doherty 1209
Instructors:
Stephen Fienberg
, Baker Hall 229B, x82723, Stephen.Fienberg@cmu.edu
Tom Mitchell, Wean
Hall 5309, x82611, 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 CoTraining .
Avrim Blum and Tom Mitchell.
Proceedings of the 11th Annual Conference on Computational Learning Theory (COLT98).

A Tutorial on Learning with Bayesian Networks,
D. Heckerman,
Microsoft Research Tech Report MSRTR9506, 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, 168197. Berlin: SpringerVerlag.

Friedman, J. H., Hastie, T. and Tibshirani, R.
"Additive Logistic Regression: a Statistical View of Boosting." (Aug. 1998)

list of MCMC papers
Assigned
Student Groups
Homeworks: