The workshop is part of the activities of the ELSA Network of Excellence, and it will focus on the issue of privacy in machine learning in general, and federated learning in particular.
The issue of privacy in machine learning has received a lot of attention by the scientific community, and several approaches have been proposed, involving differential privacy, secure multi-party computation, secure aggregation, homomorphic encryption, etc. However, the proposed solutions so far suffer from various limitations in terms of trade-offs between accuracy, privacy, efficiency, and personalization.
The purpose of this workshop is to be a forum for discussing recent advances in the above topics area, and foster collaborations among researchers interested in advancing the state-of-the-art.
If you are interested in participating in our workshop, please complete the application form provided below to reserve your spot.
