Tentative Schedule
| Date | Topic | Lecture Notes | Further Reading | Homework |
|---|---|---|---|---|
| Fundamentals | ||||
| Jan 20 | Provable Privacy: Why and How | |||
| Jan 22 | Privacy Basics I | |||
| Jan 27 | Privacy Basics II | |||
| Jan 29 | Differentially Private Gradient Descent | |||
| Feb 3 | Linear Queries | |||
| Feb 5 | Beating Global Sensitivity | |||
| Feb 10 | Inverse Sensitivity | |||
| Feb 12 | Histograms and the Binary Tree Mechanism | |||
| Optimization and Machine Learning | ||||
| Feb 17 | DP Gradient Descent, Again | |||
| Feb 19 | Rényi Differential Privacy | |||
| Feb 24 | Amplification by Subsampling and DP-SGD | |||
| Feb 26 | DP-FTRL, Correlated Noise | |||
| Multivariate Statistics | ||||
| March 3 | Mean Estimation; Subsample and Aggregate | |||
| March 5 | FriendlyCore | TCKMS21 | ||
| March 10 | Stable Estimators | |||
| Mar 12 | Stable Covariance Estimation | BHS23, AKTVZ23 | ||
| Mar 17 | The Robustness-to-Privacy Transformation |
DL09,
AUZ22
HKMN22 |
||
| Mar 19 | Sparse Mean Estimation | |||
| Mar 24 | Fingerprinting Lower Bounds I | |||
| Mar 26 | Fingerprinting Lower Bounds II | |||
| Advanced Topics | ||||
| Apr 7 | Private PAC Learning | |||
| Apr 9 | Privacy Wrappers | |||
| Apr 14 | Privacy and Generalization | |||
| Apr 16 | Amplification by Iteration | |||
| Apr 21 | Convergent Bounds on Privacy Loss | AT22 | ||
| Apr 23 | TBD | |||
| Project Presentations | ||||
| Apr 28 | Student Presentations | |||
| Apr 30 | Student Presentations | |||
| May 1 | Student Presentations | |||