Final Project

The guidelines and some recommended topics can be found here.
You have to choose your project by November 20.
Each student has to make a presentation, scheduled for the last lecture, and submit a report up to 5 pages by December 15. The LaTex format for the report can be found here.

The schedule of the final presentations:

Presenter	time (Dec 6)	Title
Sarthak	10.30 - 11.00	Differentially Private Empirical Risk Minimization
Mohammad	11.00 - 11.30	Semi-Supervised Knowledge Transfer for Deep Learning from Private Training Data
Jason	11.30 - 12.00	Node and Edge Differential Privacy for Graph Laplacian Spectra: Mechanisms and Scaling Laws
Yinying	12.00 - 12.30	Collecting Telemetry Data Privately
Alireza	12.30 - 1.00	Black-Box Differential Privacy for Interactive ML
Yuanqi	1.00 - 1.30	On the Privacy Risks of Algorithmic Recourse
Narges	1.30 - 2.00	Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget
Catherine	2.00 - 2.30	Attacks on Deidentification’s Defenses