We introduce Regularized Least Squares regression and classification.
We then introduce SVMs for classification and regression. All the above are
instances of Tikhonov regularization.
Slides for this lecture: PDF
- Rifkin. Everything Old Is New Again: A Fresh Look at Historical Approaches in Machine Learning. MIT Ph.D. Thesis, 2002.
- Evgeniou, Pontil and Poggio. Regularization Networks and Support Vector Machines Advances in Computational Mathematics, 2000.
- Rifkin, R.,. and R.A. Lippert.Notes on Regularized Least-Squares, CBCL Paper #268/AI Technical Report #2007-019, Massachusetts Institute of Technology, Cambridge, MA, May, 2007.