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Matlab
Fall 2003
Fall 2002
Fall 2001

6.867 References
References
Optional papers (also listed with lectures):

C. Burges. A Tutorial on Support Vector Machines for Pattern Recognition.
Knowledge Discovery and Data Mining, 2(2), 1998.
postscript
 R. Schapire, "A brief introduction to boosting", In Proceedings
of the Sixteenth International Joint Conference on Artificial
Intelligence, 1999. postscript
 J. Friedman, T. Hastie, and R. Tibshirani, "Additive Logistic
Regression: a Statistical View of Boosting",
postscript
Books:
 Jordan, "Introduction to Probabilistic Graphical Models", draft
version available electronically
here
(MIT only access)
 R. Duda, P. Hart, and D. Stork. "Pattern Classification", 2nd
edition, Wiley Interscience, 2001.
 C. M. Bishop. "Neural Networks for Pattern Recognition",
Oxford University Press, 1995.
 T. Mitchell, "Machine Learning". McGraw Hill, 1997.
 T. Hastie, R. Tibshirani and J. Friedman, "Elements of Statistical
Learning: Data Mining, Inference and Prediction". SpringerVerlag, 2001.
 T. Cover and J. Thomas. "Elements of Information theory",
Wiley Interscience, 1991.
