Sangshin Lee

HCFL: hybrid contribution-driven federated learning for fair and efficient optimization.

An adaptive FL framework that employs a hybrid contribution evaluation mechanism as the core principle for client selection and resource management is proposed and demonstrates that the proposed framework outperforms existing FL baselines in terms of training efficiency, data utilization, and fairness.