Schedule
Spring 2025 · Boston University · Adam Smith
Archived offering · Dates and course information refer to Spring 2025.
On smaller screens, scroll the table horizontally to see all columns.
Lecture videos (from 2021) can be found in this Google Drive folder.
| Date | Topics | Deliverables |
|---|---|---|
| Tue 1/21 | Lecture 1: Course Overview Video: Watch these two MinutePhysics videos (1, 2). They introduce some of the course topics in the context of the US Census. Lecture Slides: pdf In-class Exercises: pdf (We did not get to these in class. They are posted for reference.) |
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| Unit 1: Reconstruction Attacks | ||
| Thu 1/23 |
Lecture 2: Reconstruction Attacks I Video: part 1, part 2 Lecture Notes: pdf that goes with videos (up through 2.3). Additional optional reading on reconstruction:
In-class Exercises: pdf |
|
| Tue 1/28 | Lecture 3: Reconstruction Attacks II Lecture Notes: pdf (2.4 onward) Video: part 1, part 2 In-class Exercises: pdf |
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| Unit 2: Differential Privacy Fundamentals | ||
| Thu 1/30 | Lecture 4: Differential Privacy Fundamentals I Lecture Notes: pdf Lecture Slides (in person lecture): pdf Video (from 2021, for reference): part 1, part 2, part 3, part 4 |
Homework 1 out (pdf), due Sunday February 16, 2025. |
| Tue 2/4 | Lecture 5: Differential Privacy Fundamentals II Lecture Notes: pdf Video: part 1, part 2, part 3 In-class Exercises: pdf |
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| Thu 2/6 | Lecture 6: Exponential Mechanism and Report Noisy Max Lecture Notes: pdf Video: part 1, part 2, part 3, part 4, In-class Exercises: pdf |
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| Unit 3: The Algorithmic Toolkit | ||
| Tue 2/11 | Lecture 7: The Binary Tree Mechanism Lecture Notes: pdf Video: part 1, part 2 In-class Exercises: pdf |
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| Thu 2/13 | Lecture 8: Approximate DP In-person lecture; no advanced reading required. Lecture Notes: pdf Video: part 1, part 2 In-class Exercises: N/A |
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| Tue 2/18 | No class (Monday schedule) | |
| Thu 2/20 | Lecture 9: Advanced Composition Lecture Notes: pdf Video: part 1, part 2 In-class Exercises: pdf |
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| Tue 2/25 | Lecture 10: Recap (No lecture notes or videos.) In-class Exercises: pdf |
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| Thu 2/27 | Lecture 11: Private Empirical Risk Minimization Lecture Notes: pdf Video: part 1, part 2 In-class Exercises: pdf |
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| Tue 3/4 | Lecture 12: Private Gradient Descent Lecture Notes: pdf Video: part 1, part 2 In-class Exercises: pdf |
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| Thu 3/6 | Lecture 13: Factorization Mechanisms Lecture Notes: pdf (up to 2.3) Video: part 1, part 2 In-class Exercises: pdf |
Homework 2 out (pdf), due Friday, March 21, 2025. |
| Tue 3/12 | No class (Spring break) | Project info out (pdf). Proposals due Wednesday, March 26, 2025 |
| Thu 3/14 | No class (Spring break) | |
| Tue 3/18 | Lecture 14: DP-FTRL Slide notes: pdf Based on Kairouz, McMahan, Song, Thakkar, Thakurta, Xu (NeurIPS 2021) (as well as a few subsequent papers). |
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| Thu 3/20 | Lecture 15: The Projection Mechanism Lecture Notes: pdf (2.3 onward) Video: part 1 In-class Exercises: pdf |
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| Tue 3/25 | Lecture 16: Online Learning and Multiplicative Weights Lecture Notes: pdf (Sections 1 to 3.1) Video: part 1, part 2, part 3, part 4 In-class Exercises: pdf |
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| Thu 3/27 | Lecture 17: Synthetic Data Generation and Online Learning Lecture Notes (hand-written): pdf We covered this material in a live lecture, but here are vidoes from 2021: part 1, part 2, part 3, part 4, part 5, part 6. |
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| Tue 4/1 | Lecture 18: The Limits of Privacy Lower Bounds from Reconstruction and Membership Inference Attacks (in person) Lecture Notes: pdf |
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| Thu 4/3 | Lecture 19: Two-Player Zero-Sum Games I Lecture Notes: pdf (up to the end of 1.2) Video: part 1 (Only one video for Lec 19.) In-class excercises: pdf |
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| Tue 4/8 | Lecture 20: Two-Player Zero-Sum Games II Lecture Notes: pdf (1.3 onward) Video: part 1 part 2 part 3 In-class excercises: pdf |
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| Thu 4/13 | Lecture 21: Private Statistical Inference Lecture slides: pdf |
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| Tue 4/15 | Lecture 22: A Simple Analysis of Robust Membership Inference Attacks Hand-written Lecture Notes: pdf |
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| Thu 4/17 | Lecture 23: More on Membership Inference and Memorization Plots on membership inference: Colab Lecture Slides: pdf |
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| Tue 4/22 | Lecture 24: The Local Model Lecture slides: pdf |
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| Thu 4/24 | Lecture 24: Adaptive Data Analysis Lecture slides: pdf |
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| Tue 4/29 | Lecture 26: Private Testing of Simple Hypotheses Based on Canonne, Kamath, McMillan, Ullman, Smith (2019). See also McMillan, Ullman, Smith (2022) and Asi, Duchi, Haque, Li, Ruan (2024). |
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