Each lecture summary below provides a brief description of the topics covered, as well as a list of suggested readings for more in-depth exploration. The slide presentations from many of the lectures are also included.
| LEC # | TOPICS |
|---|---|
| 1 | The Course at a Glance Summary (PDF) |
| 2 | The Learning Problem in Perspective Summary (PDF) Slides (PDF) |
| 3 | Regularization and Reproducing Kernel Hilbert Spaces Summary (PDF) Slides (PDF) |
| 4 | Regression and Least-Squares Classification Summary (PDF) Slides (PDF) |
| 5 | Support Vector Machines for Classification Summary (PDF) Slides (PDF) |
| 6 | Generalization Bounds, Introduction to Stability Summary (PDF) Slides (PDF) |
| 7 | Stability of Tikhonov Regularization Summary (PDF) Slides (PDF) |
| 8 | Consistency and Uniform Convergence Over Function Classes Summary (PDF) Slides (PDF) |
| 9 | Necessary and Sufficient Conditions for Uniform Convergence Summary (PDF) Slides (PDF) |
| 10 | Bagging and Boosting Summary (PDF) Slides (PDF) |
| 11 | Computer Vision, Object Detection Summary (PDF) |
| 12 | Loose Ends |
| 13 | Approximation Theory Summary (PDF) Slides (PDF) |
| 14 | RKHS, Mercer Thm, Unbounded Domains, Frames and Wavelets Summary (PDF) Slides (PDF) |
| 15 | Bioinformatics Summary (PDF) |
| 16 | Text Summary (PDF) Slides (PDF) |
| 17 | Regularization Networks Summary (PDF) Slides (PDF) |
| 18 | Morphable Models for Video Summary (PDF) |
| 19 | Leave-one-out Approximations Summary (PDF) Slides (PDF) |
| 20 | Bayesian Interpretations Summary (PDF) Slides (PDF) |
| 21 | Multiclass Classification Summary (PDF) Slides (PDF) |
| 22 | Stablity and Glivenko-Cantelli Classes |
| 23 | Symmetrization, Rademacher Averages |
| Math Camp | Math Camp 1: Functional Analysis Summary (PDF) Slides (PDF) |
| Math Camp | Math Camp 2: Lagrange Multipliers/Convex Optimization Summary (PDF) |
| Extra Topic | SVM Rules of Thumb Summary (PDF) |