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Week 1 - Introduction and Privacy Attacks
Week 2 - Differential Privacy Basics I
- Aug 5
- Lab PyTorch Review
- Additional tutorials
- Aug 7
- Introduction to differential privacy (DP)
- Reading - Sec. 1.4-1.6 of Vadhan
- Aug 8
- DP - basic composition
- Reading - Sec. 2 of Steinke
- Aug 9
- HW 0 due
Week 3 - Differential Privacy Basics II
- Aug 12
- Concentration of Measure - part 1 (No lab)
- Duchi’s notes
- Aug 14
- Concentration of Measure - part 2
- Sec. 1 - 3 of Rivasplata’s note
- Aug 15
- No class (Independence Day)
- HW 1 released
Week 4 - Differential Privacy Basics III
- Aug 19
- Lab Privacy Accounting
- dp-accounting library
- Aug 21
- Concentrated DP & advanced composition
- Reading - Sec. 4.1-4.2 of Steinke
- Aug 23
- Amplification by Subsampling
- Reading - Sec. 6.1-6.3 of Steinke
Week 5 - Learning with DP I
- Aug 26
- Lab Per-sample gradients in PyTorch
- Tutorial
- Aug 28
- Rényi DP - Subsampling + Composition
- Reading - Sec. 6.4 of Steinke and Mironov et al. Optional: Sec. 6.5 and 6.4 of Steinke
- Aug 29
- Stochastic gradient descent with DP + Practical considerations
- Reading - Sec. 4.2 of Ponomareva et al. (Sec. 5 is also strongly recommended)
- Aug 30
- HW 1 due
- HW 2 released
Week 6 - Learning with DP II
- Sept 2
- Lab DP-SGD
- Sept 4
- Class Cancelled, make-up to be announced later
Theoretical Analysis of DP-SGD - Sept 5
- Private learning with Correlated Noise - part 1
- Reading - see Piazza
Week 7 - Learning with DP III
- Sept 9
- Lab Correlated noise mechanisms
- Sept 11
- Private learning with Correlated Noise - part 2
- Reading - see Piazza
- Sept 12
- Other DP-learning methods: perturbation, ensembling
- Objective perturbation: Chaudhuri et al., PATE: Papernot et al. and Papernot et al.
- Sept 15
- HW 2 due
Week 8 - Projects & Review
- Sept 16
Holiday Project Discussions- Call for Projects Released
- Sept 18
- Project Discussions
DP’s protections for reconstruction - Sept 19
- Homework Review
Reconstruction Protection via Fisher Information
Week 9 - No class
- Sept 23
- No class: work on project proposals
- Sept 25
- No class: work on project proposals
- Sept 26
- No class: work on project proposals
- Sept 27
- Project Proposals due
Week 10 - Review & Midterm
- Sept 30
- Midterm Review
- Oct 2
- Holiday
- Oct 3
- Midterm
- Oct 4
- HW3 released
Week 11 - Federated Learning and Privacy with Distributed Data
Week 12 - Protecting Against Data Reconstruction
- Oct 14
- (Online) Guest Lecture by Ashwinee Panda on Private In-Context Learning in LLMs
- Paper
- Oct 16
- DP’s protections for reconstruction
- Stock et al.
- Oct 17
- Reconstruction Protection via Fisher Information
- Guo et al.
Week 13 - Privacy in Generative AI
- Oct 21
- Project Office Hours
- Oct 23
- Copyright Protection in Generative AI
- Vyas et al.
- Oct 24
- Synthetic text generation (+ exponential mechanism)
- Amin et al. (Smith’s notes for the exponential mechanim)
- Oct 27
- Project midpoint report due
Week 14 - Advanced Topics
Week 15 - Project Presentations
Week 16 - Buffer / End-sem Week
- Nov 15
- Project final report due at noon