Lectures
| Lecturer | Varun Kanade |
| Hours | Mon, Tue, Thu: 4-5pm |
| Location | Lecture Theatre A |
| Notes | (Lecture Notes) |
Note 1. I only expect there to be about 20 hours of lectures in total. I have scheduled more hours and intend to have longer lectures at the start of term to ensure that there is enough time left if rescheduling is necessary.
Note 2. A set of lecture notes (LN) covering the entire course will be posted. These are not meant to be used as a substitute for reading the recommended textbooks and other posted reading. There might be some delay in updating the lecture notes. Should you wish to read up ahead of lectures, you may use the lecture notes posted for the Computational Learning Theory course from Michaelmas Term 2022. The lecture notes from MT2022 are complete, but I will add additional explanations, references and problems, and also fix typos. Please email me directly if you find any typos. Please make sure to make use of the most updated material when revising.
Note 3. There will be parts of suggested reading material that you struggle with or may seem not directly related to what we covered in the lecture. I suggest you skip these sections and only return to them once you've understood the material covered in the lecture and want to increase your understanding further.
Lecture Schedule
| Date | Topic | Reading |
|---|---|---|
| 09/10/2023 | Setting up the PAC Learning Framework | Chap 1.1-2 (LN) Chap 1.1-2 (KV) |
| 10/10/2023 | PAC Learning Conjunctions | Chap 1.2-3 (LN) Chap 1.2-3 (KV) Valiant's paper |
| 12/10/2023 | Hardness of learing 3-term DNF | Chap 1.4-8 (LN) Chap 1.4-7 (KV) |
| 16/10/2023 | PAC Learning; Occam's Razor | Chap 1.8, Chap 2 (LN) Chap 1.7, 2 (KV) |
| 17/10/2023 | VC Dimension; Sauer-Shelah Lemma | Chap 3.1-2 (LN) Chap 3.1-4 (KV) |
| 19/10/2023 | VC Dimension Upper Bound | Chap 3.3 (LN) Chap 3.5 (KV) |
| 23/10/2023 | VC Dimension Lower Bound; Boosting | Chap 3.4, 4 (LN) Chap 3.6 (KV) |
| 24/10/2023 | AdaBoost | Chap 4 (LN) Adaboost survey Adaboost article |
| 26/10/2023 | Cryptographic Hardness of Learning | Chap 5 (LN) Chap 6 (KV) |
| 30/10/2023 | Exact Learning with MQ + EQ | Chap 6.1-2 (LN) Chap 8.1-2 (KV) |
| 31/10/2023 | Exact Learning DFA; L* Algorithm | Chap 6.3 (LN) Chap 8.3 (KV) |
| 02/11/2023 | Learning with RCN | Chap 7.1 (LN) Chap 5.1-2 (KV) |
| 06/11/2023 | SQ Learning; Hardness of Learning PARITIES | Chap 7.2-3 (LN) Chap 7.3 (KV) |
| 07/11/2023 | Learning Real-Valued Functions; Gradient Descent |
Chap 8.1-2 (LN) Convex Opt. book (Chap. 3.1) |
| 09/11/2023 | Learning LMs, GLMs | Chap 8.4-5 (LN) Chap 3 (MRT) |
| 13/11/2023 | Rademacher Complexity | Chap 8.3 (LN) Chap 3 (MRT) |
| 14/11/2023 | (Online) Mistake-Bounded Learning |
Chap 9.1-3 (LN) Littlestone's paper |
| 16/11/2023 | Perceptron and Winnow |
Chap 9.4-5 (LN) Littlestone's paper |
| 20/11/2023 | Exponentially-weighted Forecaster; Regret |
Chap 10 (LN) MWUA Survey |