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.
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Useful reference for Ganghua Sun's lecture on 2/4/02:
Introduction to Data Mining
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COLT: Computational Learning Theory, web site
maintained by Stephen S. Kwek:
www.learningtheory.org
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Michael J. Kearns and Umesh V. Vazirani, "An Introduction to
Computational Learning Theory," MIT Press, (1994). On reserve
at the Engineering Library.
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Tom M. Mitchell, "Machine Learning," McGraw-Hill, (1997). On
reserve at the Engineering Library.
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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
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L. G. Valiant, "A theory of the learnable," Comm. ACM 27, pp. 1134-1142
(1984).
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Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, and Manfred K. Warmuth,
"Occam's razor," IPL 24, pp. 377-380 (1987).
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J. R. Quinlan, "Induction of decision trees," Machine Learning 1,
pp. 81-106 (1986).
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Michael Kearns and Yishay Mansour,
"On the boosting ability of top-down decision tree learning algorithms,"
JCSS 58, pp. 109-128 (1999).
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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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