| Date | Topic | Handout | Additional Reading |
|---|---|---|---|
| 01/11 | Introduction | Lecture 1 Slides | |
| 01/13 | A Taste of Machine Learning | Chapter 1 | |
| 01/18 | A Taste of Machine Learning | Chapter 1 | |
| 01/20 | Johnson Lindestrauss Lemma | Notes | |
| 01/25 | Johnson Lindestrauss Lemma | Notes | |
| 01/27 | A Taste of Learning Theory | Notes | |
| 02/01 | Snow Recess | No Class | |
| 02/03 | Non Parametric Density Estimation | Notes | |
| 02/08 | Non Parametric Density Estimation | Notes | |
| 02/10 | Exponential Families of Distributions | Notes | |
| 02/15 | Exponential Families of Distributions | Notes | |
| 02/17 | Conjugate Priors | Notes | http://cocosci.berkeley.edu/tom/papers/ibptr.pdf |
| 02/22 | Optimization | Notes | |
| 02/24 | Gradient Descent | Notes | |
| 03/01 | Quasi-Newton Methods | Notes | |
| 03/03 | Boosting - I | Slides | |
| 03/08 | Boosting - II | Slides | Rob Schapire Tutorial |
| 03/10 | Boosting - III | Slides | Francois Fleuret Course Notes |
| 03/15 | Spring Break - No Class | ||
| 03/17 | Spring Break - No Class | ||
| 03/22 | Midterm | ||
| 03/24 | Online Learning | Notes | |
| 03/29 | Online Learning | Notes | |
| 03/31 | Logistic Regression | Notes | |
| 04/05 | Support Vector Machines | Notes | |
| 04/07 | Support Vector Machines | Notes | |
| 04/12 | Support Vector Machines | Notes | |
| 04/14 | Optimization for Machine Learning | Slides | |
| 04/19 | Graph Kernels | Slides |
