FedDAG: Clustered Federated Learning via Global Data and Gradient Integration for Heterogeneous Environments

Researchers introduce FedDAG, a new clustered federated learning framework that improves AI model training across heterogeneous client environments. The system combines data and gradient similarity metrics for better client clustering and uses a dual-encoder architecture to enable knowledge sharing across clusters while maintaining specialization.