Author:
Wang Lingfu,Xiong Zuobin,Luo Guangchun,Li Wei,Chen Aiguo
Publisher
Springer Nature Switzerland
Reference30 articles.
1. Cho, Y.J., Wang, J., Joshi, G.: Client selection in federated learning: convergence analysis and power-of-choice selection strategies. arXiv preprint arXiv:2010.01243 (2020)
2. Cong, Y., et al.: Ada-FFL: adaptive computing fairness federated learning. CAAI Trans. Intell. Technol. (2023)
3. Du, W., Xu, D., Wu, X., Tong, H.: Fairness-aware agnostic federated learning. In: Proceedings of the 2021 SIAM International Conference on Data Mining (SDM), pp. 181–189. SIAM (2021)
4. Ezzeldin, Y.H., Yan, S., He, C., Ferrara, E., Avestimehr, A.S.: Fairfed: enabling group fairness in federated learning. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 37, pp. 7494–7502 (2023)
5. Hamidi, S.M., Damen, O.: Fair wireless federated learning through the identification of a common descent direction. IEEE Commun. Lett. (2024)