Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints
This paper studies federated learning for nonparametric regression in the context of distributed samples across different servers, each adhering to distinct differential privacy constraints. The setting we consider is heterogeneous, encompassing both varying sample sizes and differential privacy constraints across serv...