This course provides a foundational perspective on individual privacy in the context of statistical data analysis and machine learning. The focus will be on differential privacy, a rigorous mathematical formulation of individual privacy. We will study privacy concerns and attacks, the framework of differential privacy, state-of-the-art differentially private algorithms for data analysis and machine learning, and (time permitting) connections to adaptive data analysis and fair classification.
A past website for the course can be consulted
SPECIAL NOTE for Fall 2020: I expect that all lectures in this course will be remote (via Zoom)