Date	Lecture	Readings	Logistics
Fri 01/08	Lecture #1 : Overview of Statistical Machine Learning [ slides notes ]	Vapnik, V. (1991). Principles of risk minimization for learning theory. Advances in neural information processing systems, 4. PDF Breiman, L. (2001). Statistical modeling: The two cultures (with comments and a rejoinder by the author). Statistical science, 16(3):199-231. PDF Section 12.2: The Support Vector Classifier (The Elements of Statistical Learning) On a class of of Perceptions (translated version) PDF
Fri 01/16	Lecture #2 : Approximation error and estimation error [ slides notes ]	chapter 4 of Cucker, F., & Zhou, D. X. (2007). Learning theory: an approximation theory viewpoint (Vol. 24). Cambridge University Press.
Fri 01/23	Lecture #3 : Uniform concentration inequality [ slides notes ]	Lugosi, G. Concentration-of-measure inequalities. PDF