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) |
