IEEE

FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors

Abstract: Federated Learning (FL) has emerged as a promising framework for distributed machine learning, enabling collaborative model training without sharing local data, thereby preserving privacy ...
IEEE

Flagger: Cooperative Acceleration for Large-Scale Cross-Silo Federated Learning Aggregation

Abstract: Cross-silo federated learning (FL) leverages homomorphic encryption (HE) to obscure the model updates from the clients. However, HE poses the challenges of complex cryptographic computations ...