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Haijin Wang

2 accepted papers

2024

FedLF: Layer-Wise Fair Federated Learning

AAAI 2024technical

Fairness has become an important concern in Federated Learning (FL). An unfair model that performs well for some clients while performing poorly for others can reduce the willingness of clients to participate. In this work, we identify a direct cause of unfairness in FL - the use of an unfair direct…

2023

FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance

AAAI 2023technical

Fairness has been considered as a critical problem in federated learning (FL). In this work, we analyze two direct causes of unfairness in FL - an unfair direction and an improper step size when updating the model. To solve these issues, we introduce an effective way to measure fairness of the model…