Assumed background. We expect that the participants have thorough computer science knowledge and an undergraduate-level understanding of elementary cryptography and its basic mathematical foundations. We expect the participants to have previously seen formal proof techniques of mathematics, theoretical computer science, and cryptography. Therefore, participants should either be mathematicians with a strong background in computer science or computer scientists with some experience in theoretical computer science.

Main School Content. We will equip the participants with a basic understanding of the foundational results from Privacy-Preserving Machine Learning and an overview of state-of-the-art results and promising research directions. At the beginning of the school, we will provide a general introduction to machine learning and secure computation. More technical lectures on concrete, practical solutions, and attacks will follow this. 

The detailed program will be published soon. It will be very similar to the one of the PPML’22 school in Copenhagen.  The list of the lecturers is available here.

The school will start on Monday, July 31 morning, and end on Thursday, August 3 afternoon.