Schedule
Deadlines
- Homework 1: 9/26
- Homework 2: 10/17
- Homework 3: 11/14
- Homework 4: 12/6
- Final: 12/3
Lecture Schedule (Tentative)
| Week | Lecture | Date | Topic | Readings | Slides Notes |
|---|---|---|---|---|---|
| Week 1 | Lecture 1 | (8/31) | Course Overview | Slides | |
| Week 1 | Lecture 2 | (9/1) | Reconstruction Attacks (Part 1) | Reading | Slides Note |
| Week 1 | (9/3) | No Recitation | |||
| Week 2 | (9/6) | Labor Day: No Class | |||
| Week 2 | Lecture 3 | (9/8) | Reconstruction Attacks (Part 2) | Reading | Slides Note |
| Week 2 | Recitation 1 | (9/10) | Probability Review (HW 0) | HW 0 | |
| Definitions and Basic Techniques | |||||
| Week 3 | Lecture 4 | (9/13) | Definition of Differential Privacy Randomized Response |
Slides Note |
|
| Week 3 | Lecture 5 | (9/15) | Laplace Mech. (Part 1) | Reading | Slides Note |
| Week 3 | Recitation 2 | (9/17) | DP Review | ||
| Week 4 | Lecture 6 | (9/20) | Laplace Mech. (Part 2) | Slides Note |
|
| Week 4 | Lecture 7 | (9/22) | Properties of DP (Part 1) | Slides Note |
|
| Week 4 | Recitation 3 | (9/24) | DP/Laplace Review | ||
| Week 5 | Lecture 8 | (9/27) | Properties of DP (Part 2) | Slides Note |
|
| Week 5 | Lecture 9 | (9/29) | Selection problem (Part 1) Exponential Mech. |
Slides Note |
|
| Week 5 | Recitation 4 | (10/1) | Review/HW1 | ||
| Week 6 | Lecture 10 | (10/4) | Selection problem (Part 2) | Slides Note |
|
| Week 6 | Lecture 11 | (10/6) | Approximate DP Gaussian Mech. (Part 1) |
Slides Note |
|
| Week 6 | Recitation 5 | (10/8) | Review (in-person) | ||
| Week 7 | Lecture 12 | (10/11) | Approximate DP Gaussian Mech. (Part 2) |
Slides Note |
|
| Week 7 | Lecture 13 | (10/13) | No Class: Optional guest lecture on zoom | ||
| Week 7 | Recitation 6 | (10/15) | Review | ||
| Private Machine Learning | |||||
| Week 8 | Lecture 14 | (10/18) | Basic Machine Learning | Slides Note |
|
| Week 8 | Lecture 15 | (10/20) | Basic Machine Learning Gradient descent |
Slides Note |
|
| Week 8 | Recitation 7 | (10/22) | ML Review | ||
| Week 9 | Lecture 16 | (10/25) | Private Gradient Descent (Part 1) | Slides DP-SGD Note Adv. Comp. Note |
|
| Week 9 | Lecture 17 | (10/27) | Private Gradient Descent (Part 2) | Slides | |
| Week 10 | Lecture 18 | (11/1) | DP ML PATE |
Slides | |
| Week 10 | Lecture 19 | (11/3) | DP Synthetic Data (Part 1) | Slides | |
| Week 10 | (11/5) | No Recitation Day for Community Engagement |
|||
| Week 11 | Lecture 20 | (11/8) | DP Synthetic Data (Part 2) | Slides | |
| Fairness in Machine Learning | |||||
| Week 11 | Lecture 21 | (11/10) | Fair ML (Part 1) | Slides | |
| Week 12 | Lecture 22 | (11/15) | Fair ML (Part 2) | Slides | |
| Week 12 | Lecture 23 | (11/17) | Fair ML (Part 3) | Slides | |
| Week 13 | Lecture 24 | (11/22) | Fairness and Causal Inference | Slides | |
| Week 13 | (11/24) | Thanksgiving: No Class | |||
| Week 14 | Lecture 25 | (11/29) | DP and Census guest lecture |
||
| Week 14 | Lecture 26 | (12/1) | Review (Last Lecture) |
Acknowledgement: Some of course materials are based on those developed by Gautam Kamath, Jonathan Ullman, Adam Smith, and Aaron Roth.