Description
SVMs from a geometric perspective as well as the regularization perspective. We introduce the basic tools of optimization, including duality, to analyze the SVM problem.Slides
Slides for this lecture: PDFSuggested 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.
- V. N. Vapnik. The Nature of Statistical Learning Theory. Springer, 1995.