Class 05: Logistic Regression and Support Vector Machines

Instructor: Lorenzo Rosasco

Slides

Slides for this lecture: PDF

Class Reference Material

L. Rosasco, T. Poggio, Machine Learning: a Regularization Approach, MIT-9.520 Lectures Notes, Manuscript, Dec. 2017

Chapter 4 - Regularization Networks
Appendix - Convex Optimization

Note: The course notes, in the form of the circulated book draft is the reference material for this class. Related and older material can be accessed through previous year offerings of the course.

Further Reading

• E. De Vito, L. Rosasco, A. Caponnetto, M. Piana and A. Verri, Some Properties of Regularized Kernel Methods, The Journal of Machine Learning Research, 2004.
• S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University Press, 2009.