Privacy-Preserving Computation for Machine Learning (CS 595-02)

This course is a graduate-level and application-oriented course in security/privacy and machine learning. In this course, you will learn the fundamental techniques to enable privacy-preserving machine learning based on recent advancements in cryptography, with an in-depth focus on fully homomorphic encryption (FHE). This course is application-oriented with some necessary theoretical concepts. Specifically, this course will cover the basics of machine learning, the foundations of FHE, different FHE schemes, and the programming techniques of using FHE for machine learning. This course includes paper reading on recent advanced topics and hands-on projects to use well-developed software libraries to implement privacy-preserving machine learning kernels and models.