Beyond Non-IID: Learner--Client Distribution Mismatch in Federated Learning
This paper considers the practical setting where the learner keeps a small proxy dataset, and proposes a dynamic, influence-aware client selection framework that estimates each client's potential utility to the learner's optimization objective using proxy influence signals on a learner-specific proxy set.