Distribution-Free Fair Federated Learning with Small Samples

Qichuan Yin, Zexian Wang, Junzhou Huang +2

As federated learning gains increasing importance in real-world applications due to its capacity for decentralized data training, addressing fairness concerns across demographic gr…