Mitigating Group Bias in Federated Learning for Heterogeneous Devices

13 September 2023

Papers citing "Mitigating Group Bias in Federated Learning for Heterogeneous Devices"

7 / 7 papers shown

Title
FinP: Fairness-in-Privacy in Federated Learning by Addressing Disparities in Privacy Risk Tianyu Zhao Mahmoud Srewa Salma Elmalaki 95 1 0 25 Feb 2025
Unified Group Fairness on Federated Learning Fengda Zhang Kun Kuang Yuxuan Liu Long Chen Chao-Xiang Wu Fei Wu Jiaxun Lu Yunfeng Shao Jun Xiao FedML 55 20 0 09 Nov 2021
Improving Fairness for Data Valuation in Horizontal Federated Learning Zhenan Fan Huang Fang Zirui Zhou Jian Pei M. Friedlander Changxin Liu Yong Zhang TDI FedML 27 47 0 19 Sep 2021
Enforcing fairness in private federated learning via the modified method of differential multipliers Borja Rodríguez Gálvez Filip Granqvist Rogier van Dalen M. Seigel FedML 40 52 0 17 Sep 2021
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
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,203 0 23 Aug 2019
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 144 1,685 0 14 Apr 2018