Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses

Understand

This paper studies federated learning (FL)--especially cross-silo FL--with data from people who do not trust the server or other silos.

• In this setting, each silo (e.g.
• hospital) has data from different people (e.g.
• patients) and must maintain the privacy of each person's data (e.g.