| Date | Topics | Scribed lecture notes | Recommended reading | Announcements |
| Wed. 09/04 | Class overview and logistics,
PAC Learning, ERM | Course overview
Scribed Lecture 1 & 2 | MRT Chapter 2,
SB Chapters 2, 3 | Homework 0 released. |
| Fri. 09/06 | PAC Learning (cont'd),
Agnostic PAC Learning | Scribed Lecture 1 & 2 | MRT Chapter 2,
SB Chapters 4 | |
| Mon. 09/09 | Approximation error vs estimation error,
Rademacher complexity | Scribed Lecture 3 | MRT Chapter 3,
SB Chapter 6 | Homework 1 released. |
| Wed. 09/11 | Rademacher complexity (cont'd),
Sub-Gaussian random variables | Scribed Lecture 4 | MRT Chapter 3,
SB Chapter 6 | |
| Fri. 09/13 | Growth function, VC dimension | Scribed Lecture 5 | MRT Chapter 3,
SB Chapter 6 | Homework 0 due on 09/14. |
| Mon. 09/16 | Proof of Sauer's lemma,
Lower bounds for point estimation | Scribed Lecture 6 | MRT Chapter 3,
SB Chapter 6 | Solutions to
Homework 0 posted. |
| Wed. 09/18 | Lower bounds for point estimation (cont'd),
Average risk vs minimax optimality | Scribed Lecture 7 | Lectures 7, 8, 9, 10 from
Lester Mackey's class | |
| Fri. 09/20 | From estimation to hypothesis testing | Scribed Lecture 8 | JD Chapter 7 | |
| Mon. 09/23 | Neyman-Pearson test, LeCam's method | Scribed Lecture 9 | JD Chapter 7 | |
| Wed. 09/25 | LeCam's method examples (cont'd),
Review of Information Theory | Scribed Lecture 10 | JD Chapter 7,
Cover & Thomas Chapter 2 | Homework 2 released. |
| Fri. 09/27 | Review of Information Theory (cont'd)
Fano's inequality, Fano's method | Scribed Lecture 11 | JD Chapter 7 | Homework 1 due on 09/28. |
| Mon. 09/30 | Constructing alternatives for Fano's method,
Varshamov-Gilbert Lemma | Scribed Lecture 12 | JD Chapter 7 | |
| Wed. 10/02 | Tight packings and metric entropty,
Lower bounds for nonparametric regression | Scribed Lecture 13 | AT Chapter 2.5 | Solutions to
Homework 1 posted. |
| Fri. 10/04 | Upper bounds for nonparametric regression,
Lower bounds for nonparametric density estimation | Scribed Lecture 14 | AT Chapter 1.2, 1.5, 2.5 | |
| Mon. 10/07 | Kernel density estimation, Lower bounds for
prediction problems, Classification in a VC class revisited | Scribed Lecture 15 | AT Chapter 1.5,
MRT Chapter 2 | |
| Wed. 10/09 | Stochastic bandits introduction,
The upper confidence bound (UCB) algorithm | Scribed Lecture 16 | LS Chapters 1, 2, 4, 7 | Homework 3 released. |
| Fri. 10/11 | The UCB algorithm (cont'd),
Lower bounds for stochastic bandits | Scribed Lecture 17 | LS Chapter 7 | Homework 2 due on 10/12. |
| Mon. 10/14 | Lower bounds for K-armed bandits (cont'd)
Linear bandits | | LS Chapter 19 | |
| Wed. 10/16 | Linear bandits (cont'd),
Martingale concentration | Scribed Lecture 19 | LS Chapter 20 | |
| Fri. 10/18 | Introduction to online learning,
The experts problem and Hedge algorithm | Scribed Lecture 20 | FO Chapter 7 | Preliminary draft of
project due on 10/19. |
| Mon. 10/21 | Adversarial Bandits and the EXP3 algorithm,
Lower bounds for adversarial bandits | Scribed Lecture 21 | FO Chapter 10,
LS Chapter 11 | |
| Wed. 10/23 | Class canceled | | | |
| Fri. 10/25 | Contextual bandits and the EXP4 algorithm,
Online convex optimization introduction | Scribed Lecture 22 | LS Chapter 18,
FO Chapter 7 | Homework 3 due on 10/26.
Homework 4 partially
released on 10/26. |
| Mon. 10/28 | Convexity review
Follow the (regularized) leader | Scribed Lecture 23 | FO Chapter 7 | |
| Wed. 10/30 | FTRL with strongly convex regularizers,
FTRL examples, online gradient descent | Scribed Lecture 24 | FO Chapter 7 | |
| Fri. 11/01 | Follow the perturbed leader (FTPL),
FTPL for the experts problem | Scribed Lecture 25 | Kalai & Vempala, 2005 | HW4updated on 11/02 |
| Mon. 11/04 | FTPL (cont'd), Online shortest paths | Scribed Lecture 26 | Kalai & Vempala, 2005,
Karlin & Peres Ch 18 | |
| Wed. 11/06 | Learning in games | Scribed Lecture 27 | Karlin & Peres Ch 18 | |
| Fri. 11/08 | Learning in games (cont'd) | | Karlin & Peres Ch 18 | Homework 4 due on 11/09. |
| End of class |
| Sat. 11/16 | | | | Project questions (with
solutions) due on 11/16. |
Sat. 11/16 –
Sun 11/24 | Take-home exam |
| Sat. 12/7 |
| | | Solutions to assigned project
questions due on 12/7.
|