18.465 | Spring 2007 | Graduate

Topics in Statistics: Statistical Learning Theory

Readings

Vapnik, Vladimir Naumovich. The Nature of Statistical Learning Theory. New York, NY: Springer, 1998. ISBN: 9780387945590.

———. Statistical Learning Theory. New York, NY: Wiley, 1998. ISBN: 9780471030034. (Acid-free paper.)

Ledoux, Michel, and Michel Talagrand. Probability in Banach Spaces: Isoperimetry and Processes. New York, NY: Springer-Verlag, 1991. ISBN: 9780387520131.

van der Vaart, Aad W., and Jon A. Wellner. Weak Convergence and Empirical Processes: With Applications to Statistics. New York, NY: Springer, 2000. ISBN: 9780387946405.

Anthony, Martin, and Peter L. Bartlett. Neural Network Learning: Theoretical Foundations. New York, NY: Cambridge University Press, 1999. ISBN: 9780521573535.

Devroye, Luc, László Györfi, and Gábor Lugosi. A Probabilistic Theory of Pattern Recognition. New York, NY: Springer, 1997. ISBN: 9780387946184.

Additional Readings

Talagrand, M. “Concentration of Measure and Isoperimetric Inequalities in Product Spaces.” Publ Math IHES 81 (1995): 73-203.

Computational Learning Theory Web site

Learning Theory Resources, Lecture Notes, Tutorials, etc.

Course Info

Departments
As Taught In
Spring 2007
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