Privacy-preserving Machine Learning and Privacy in Distributed Settings

Workshop 2 is part of the Data Privacy in Machine Learning P1 program. It will focus on privacy in limited-trust settings, with particular interest in approaches that bring together ideas from differential privacy, decentralized learning, secure computation, and cryptography.

The program includes invited talks by Christoph Lampert, Christian Rechberger, Edwige Cyffers, Christian Weinert, and Tamer Mour, as well as contributed talks selected through the call for contributions. The first day of the workshop will be a day of tutorials on differentially private machine learning and cryptography.