IEEE

Adaptive Federated Learning With Reinforcement Learning-Based Client Selection for Heterogeneous Environments

Abstract: This study introduces an Adaptive Federated Learning (AFL) framework designed to address the challenges of data heterogeneity, resource imbalance, and communication constraints in ...
IEEE

Empowering Clients: Self-Adaptive Federated Learning for Data Quality Challenges

Abstract: Federated Learning (FL) enables collaborative model training across distributed clients, but the global model’s performance often degrades due to variable data quality and reliability at the ...