Federated Learning (FL) is a learning paradigm where multiple nodes collaboratively train model by only exchanging updates or parameters. This enables to keep data locally, therefore enhancing privacy - statement requiring nuance, e.g. memorization of training in language models. Depending on the application, number samples that each node contains can be very different, which impact and final p...