STAT 598Y: Statistical Learning Theory

Time: TR: 10:30-11:45am
Location: REC 117
Instructor: Jian Zhang (office: HAAS 226)
Office Hours: By appointment
Course Info: SYLLABUS   NOTES    HOMEWORKS    READINGS

Fall 2009 Schedule of STAT 598Y: Statistical Learning Theory
Date Topic Homework Notes Readings
Aug 25 Introduction to Supervised Learning   lecture1 [HTF] chap1,2; [DGL] chap1,2;
Aug 27 Risk Minimization   lecture2  
Sep 1 Generalization Error Bounds   lecture3  
Sep 3 Concentration Inequalities homework1    
Sep 8 PAC Learning      
Sep 10 PAC Learning   lecture4  
Sep 15 Growth Function and VC dimension   lecture5 [DGL] chap12, 13
Sep 17 Sauer's Lemma      
Sep 22 Generalization Bound for Infinite Function Class   lecture6  
Sep 24 Glivenko Cantelli Theorem homework2 lecture7  
Sep 29 Rademacher Complexity   lecture8  
Oct 1 Covering Number   lecture9  
Oct 6 The perceptron algorithm and linear SVM   lecture10 [HTF]: chap 4, 5, 12
Oct 8 convex optimization and duality      
Oct 13 Oct Break, no class     [HTF]: chap 5
Oct 15 SVM Dual problem homework3 lecture11  
Oct 20 Hilbert Space and RKHS      
Oct 22 RKHS     [HTF]: chap 10
Oct 27 Representer Theorem and Kernel Methods   lecture12  
Oct 29 Guest Lecture: Nesterov's Method   Nesterov's Method  
Nov 3 Guest Lecture: Nesterov's Method      
Nov 5 Voting Classifiers and Boosting   lecture13  
Nov 10 Maximum Likelihood Estimation   lecture14  
Nov 12 MLE      
Nov 17 M-Estimators     sec 5 of van der Geer: EP theory and Applications
Nov 19 Chaining and increments of EP     sec 6.5 of van der Geer
Nov 24        
Nov 26 No Class - Thanksgiving Break
Dec 1        
Dec 3        
Dec 8 Project Presentation      
Dec 10 Project Presentation      

Acknowledgement: A significant part of the notes was taken from lecture notes of STAT-241B at UC Berkeley.