This is a reading course for students who are interested in the theoretical foundation of machine learning to learn modern techniques to analyze machine learning algorithms. Students should have backgrounds on mathematical analysis, linear algebra, applied statistics, probability and statistical machine learning or some related CS equivalence. Students read the lecture notes and present in class.