Difference between revisions of "Support Vector Machines Old Kiwi" - Rhea

Revision as of 16:40, 30 March 2008

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

• http://en.wikipedia.org/wiki/Support_vector_machine

• `A Practical Guide to Support Vector Classification: Mainly created for beginners, it quickly explains how to use the libsvm.

• `A Tutorial on Support Vector Machines for Pattern Recognition

• `Support Vector Machines for 3D Object Recognition

• 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.

• Purdue link to SVM

• ACM link to SVM

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.