Ying-Zhu Liu

Distributionally Robust Federated Learning with Multi-Source Data

A global ambiguity set is constructed as the union of admissible mixtures of local ambiguity sets that allows client-specific ambiguity radii and admits a client-wise separable reformulation and establishes a high-probability out-of-sample performance guarantee.