#
Regularized Least-Squares and Support Vector Machines

Lorenzo Rosasco

## Description

We introduce two intances of Tikhonov regularization induced by the square and hinge loss functions.
In particular we derive and compare their computational properties.
## Slides

Slides for this lecture: PDF
## Suggested Reading

- 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.
- V. N. Vapnik.
**The Nature of Statistical Learning Theory.** Springer,
1995.