IEEE

Adaptive Model Aggregation in Federated Learning Based on Model Accuracy

Abstract: Federated learning is useful when predicting user preferences due to its ability to keep user data private. As such, certain data samples may be more useful than others. For instance, with a ...
IEEE

PRFL: Achieving Efficient Robust Aggregation in Privacy-Preserving Federated Learning

Abstract: Robust Privacy-Preserving Federated Learning (PPFL) is a secure distributed machine learning paradigm designed for untrusted environments, aiming to ...