| SES # | TOPICS | LECTURERS |
|---|---|---|
| 1 | The Course at a Glance | TP |
| 2 | The Learning Problem in Perspective | TP |
| 3 | Reproducing Kernel Hilbert Spaces | AC |
| 4 | Regression and Least-Squares Classification | RR |
| 5 | Support Vector Machines for Classification | RR |
| 6 | Manifold Regularization | AC |
| 7 | Unsupervised Learning Techniques | AC |
| 8 | Multiclass | RR |
| 9 | Ranking | Guest Lecturer: Giorgos Zacharia |
| 10 | Boosting and Bagging | AR |
| 11 | Computer Vision Object Detection | Guest Lecturer: Stan Bileschi |
| 12 | Online Learning | Guest Lecturer: Sanmay Das and AC |
| 13 | Loose Ends Project Discussions | |
| 14 | Generalization Bounds Introduction to Stability | AR |
| 15 | Stability of Tikhonov Regularization | AR |
| 16 | Uniform Convergence Over Function Classes | AR |
| 17 | Uniform Convergence for Classification VC-dimension | AR |
| 18 | Neuroscience | Guest Lecturer: Thomas Serre |
| 19 | Symmetrization Rademacher Averages | AR |
| 20 | Fenchel Duality | Guest Lecturer: Ross Lippert and RR |
| 21 | Speech / Audio | Guest Lecturer: Jake Bouvrie |
| 22 | Active Learning | Guest Lecturer: Claire Monteleoni |
| 23 | Morphable Models for Video | Guest Lecturer: Tony Ezzat |
| 24 | Bioinformatics | Guest Lecturer: Sayan Mukherjee |
| 25 | Project Presentations | |
| 26 | Project Presentations (cont.) | |
| Math Camp 1: Functional Analysis | AC | |
| Math Camp 2: Probability Theory | AR |