Lectures
Lecturer | Varun Kanade |
Hours | 16h-17h30 Monday, Tuesday and Thursday |
Location | Lecture Theatre A (Department of Computer Science) |
Notes | (Draft 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 for pandemic-related reasons.
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 follow the material posted on the Computational Learning Theory course from Michaelmas Term 2018. The only difference between the MT2018 notes and the new ones is an attempt at serialization. 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 |
---|---|---|
11/10/2021 | Setting up the PAC Learning Framework | Chap 1.1-2 (LN) Chap 1.1 (KV) |
12/10/2021 | Learning Conjunctions | Chap 1.2-3 (LN) Chap 1.2-3 (KV) Valiant's paper |
14/10/2021 | Hardness of Learning 3-term DNF; PAC Learning | Chap 1.4-6 (LN) Chap 1.4-5 (KV) |
18/10/2021 | Occam's Razor; Consistent Learning | Chap 2, Chap 3.5 (LN) Chap 2 (KV) |
19/10/2021 | VC Dimension, Sauer's Lemma | Chap 3.1-2 (LN) Chap 3.1-4 (KV) |
21/10/2021 | VC Dimension: Sample Complexity Bounds | Chap 3.3 (LN) Chap 3.5 (KV) |
25/10/2021 | VC Dimension: Sample Complexity Bounds Boosting |
Chap 3.4, 4.1 (LN) Chap 3.6 (KV) |
26/10/2021 | Adaboost |
Chap 4.2 (LN) Adaboost survey Adaboost article |
28/10/2021 | Cryptographic Hardness of Learning |
Chap 5 (LN) Chap 6 (KV) Article on shallow circuits for arithmetic operations |
01/11/2021 | Reductions Exact Learning using MQs + EQs |
Chap 6 (LN) Chap 7, 8 (KV) |
02/11/2021 | Learning DFAs using MQs + EQs |
Chap 6 (LN) Chap 8 (KV) |
04/11/2021 | Learning with Random Classification Noise SQ Learning |
[notes] Chap 5 (KV) |
08/11/2021 | SQ Learning Hardness of Learning PARITIES |
[notes] Chap 5 (KV) |
09/11/2021 | Learning Real-Valued Functions Convex Optimization |
[notes] Convex Opt. book (Chap. 3.1) |
11/11/2021 | Learning Real-Valued Functions Rademacher Complexity |
[notes] Chap 3 (MRT) |
15/11/2021 | Rademacher Complexity |
[notes] Chap 3 (MRT) |
16/11/2021 | Online Learning Mistake-bounded Learning |
[notes] [older notes] |
18/11/2021 | Perceptron and Winnow |
[notes] [older notes] Littlestone's paper |
22/11/2021 | Online Learning with Expert Advice |
[notes] MWUA Survey |