Computer Science 663b - Machine Learning

Dana Angluin

Spring 2002


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References


Site for support vector machines and kernel methods: www.kernel-machines.org Burges's tutorial paper is available in the tutorial section of the site.
Useful reference for Ganghua Sun's lecture on 2/4/02: Introduction to Data Mining
COLT: Computational Learning Theory, web site maintained by Stephen S. Kwek: www.learningtheory.org
Michael J. Kearns and Umesh V. Vazirani, "An Introduction to Computational Learning Theory," MIT Press, (1994). On reserve at the Engineering Library.
Tom M. Mitchell, "Machine Learning," McGraw-Hill, (1997). On reserve at the Engineering Library.
Ian H. Witten and Eibe Frank, "Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations," Morgan-Kaufmann (1999). Associated software: Weka 3: Machine Learning Software in Java
L. G. Valiant, "A theory of the learnable," Comm. ACM 27, pp. 1134-1142 (1984).
Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, and Manfred K. Warmuth, "Occam's razor," IPL 24, pp. 377-380 (1987).
J. R. Quinlan, "Induction of decision trees," Machine Learning 1, pp. 81-106 (1986).
Michael Kearns and Yishay Mansour, "On the boosting ability of top-down decision tree learning algorithms," JCSS 58, pp. 109-128 (1999).
Robert E. Schapire's homepage has a section on boosting: Boosting, with his most recent overview paper: "The boosting approach to machine learning: an overview."

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Last modified: 11 February 2002