Chenchen Lin

Domain Sensitive Federated Learning with Fisher-Informed Pruning

Federated Learning (FL) serves as a prominent distributed training paradigm, enabling devices to collaboratively train a shared model with local data. However, in practice, clients generally possess data from multiple distributional domains, posing significant challenges to efficiency and generaliza