A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning

Dario Filatrella, Ragnar Thobaben, Mikael Skoglund

We study expected generalization bounds for the Hierarchical Federated Learning (HFL) setup using Wasserstein distance. We introduce a generalized framework in which data is sample…