FedOAED: Improving Data Privacy and Availability in Federated Learning

This research explores a novel approach to federated learning, addressing the challenges of heterogeneous data and limited client availability in on-device autoencoder denoising. The study's focus on privacy-preserving techniques is important in the current landscape of AI.