Revision as of 17:40, 30 March 2008 by Zhu0 (Talk)

Course Topics

This page and its subtopics discusses about Support Vector Machines

Lectures discussing Support Vector Machines: Lecture 11, Lecture 12 and Lecture 13.


Useful Links

  • svms.org:Here is a good webpage containing links to effective Support Vector Machines packages, written in C/C++. Matlab, applicable for binary/multi- calss classifications.

Journal References

  • M.A. Aizerman, E.M. Braverman, L.I. Rozoner. Theoretical foundations of the potential function method in pattern recognition learning. Automation and Control, 1964, Vol. 25, pp. 821-837.
  • Bernhard E. Boser and Isabelle M. Guyon and Vladimir N. Vapnik. A training algorithm for optimal margin classifiers. COLT '92: Proceedings of the fifth annual workshop on Computational learning theory. 1992. Pittsburgh, PA.

Alumni Liaison

Abstract algebra continues the conceptual developments of linear algebra, on an even grander scale.

Dr. Paul Garrett