Resources on Regularization

Presentations

• Main presentation
• Experiments results
• Presentation on PAC learning (Andrew W. Moore - Carnegie Mellon)
• Presentation on SVMs (Andrew W. Moore - Carnegie Mellon)

Papers

• SVM Tutorial (Christopher Burges)

Software

• SVM Applet (LIBSVM)

References

• Support Vector Machines and other kernel-based learning methods (John Shawe-Taylor & Nello Cristianini.  Cambridge University Press, 2000 )
• The Nature of Statistical Learning Theory (Vladimir Vapnik. Springer-Verlag, 1995)
• Kernel Methods for Pattern Analysis (John Shawe-Taylor & Nello Cristianini. Cambridge University Press, 2004)
• Introduction to Machine Learning (Ethem Alpaydin. The MIT Press, October 2004)