Improving Fairness for Data Valuation in Horizontal Federated Learning

Improving Fairness for Data Valuation in Horizontal Federated Learning

19 September 2021

Zhenan Fan

Changxin Liu

Yong Zhang

Papers citing "Improving Fairness for Data Valuation in Horizontal Federated Learning"

7 / 7 papers shown

Title
An Empirical Study of the Impact of Federated Learning on Machine Learning Model Accuracy Haotian Yang Z. Wang Benson Chou Sophie Xu Hao Wang Jingxian Wang Qizhen Zhang FedML 88 0 0 26 Mar 2025
Ten Challenging Problems in Federated Foundation Models Tao Fan Hanlin Gu Xuemei Cao Chee Seng Chan Qian Chen ... Y. Zhang Xiaojin Zhang Zhenzhe Zheng Lixin Fan Qiang Yang FedML 73 4 0 14 Feb 2025
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning Zhangchen Xu Fengqing Jiang Luyao Niu Jinyuan Jia Bo Li Radha Poovendran FedML 27 1 0 31 May 2024
A Survey of Federated Evaluation in Federated Learning Behnaz Soltani Yipeng Zhou Venus Haghighi John C. S. Lui FedML 20 12 0 14 May 2023
FederatedTrust: A Solution for Trustworthy Federated Learning Pedro Miguel Sánchez Sánchez Alberto Huertas Celdrán Ning Xie Gérome Bovet Gregorio Martínez Pérez Burkhard Stiller 25 21 0 20 Feb 2023
FedFair: Training Fair Models In Cross-Silo Federated Learning Lingyang Chu Lanjun Wang Yanjie Dong J. Pei Zirui Zhou Yong Zhang FedML 56 40 0 13 Sep 2021
Efficient Client Contribution Evaluation for Horizontal Federated Learning Jie Zhao Xinghua Zhu Jianzong Wang Jing Xiao FedML 24 28 0 26 Feb 2021