Yongzhe Jia

A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments

This work proposes PHP-FL, a novel model-heterogeneous FL method that explicitly addresses scenarios with varying client participation probabilities to enhance both model accuracy and performance fairness, and introduces a Dual-End Aligned ensemble Learning (DEAL) module.