Fast Federated Learning in the Presence of Arbitrary Device
Unavailability
Fast Federated Learning in the Presence of Arbitrary Device
Unavailability
Federated Learning (FL) coordinates with numerous heterogeneous devices to collaboratively train a shared model while preserving user privacy. Despite its multiple advantages, FL faces new challenges. One challenge arises when devices drop out of the training process beyond the control of the central server. In this case, the convergence of …