Fairness and Privacy-Preserving in Federated Learning: A Survey

Fairness and Privacy-Preserving in Federated Learning: A Survey

14 June 2023

Taki Hasan Rafi

Faiza Anan Noor

Papers citing "Fairness and Privacy-Preserving in Federated Learning: A Survey"

14 / 14 papers shown

Title
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 16 1 0 01 Jun 2024
Secure Shapley Value for Cross-Silo Federated Learning (Technical Report) Shuyuan Zheng Yang Cao Masatoshi Yoshikawa FedML 58 24 0 11 Sep 2022
"You Can't Fix What You Can't Measure": Privately Measuring Demographic Performance Disparities in Federated Learning Marc Juárez Aleksandra Korolova FedML 28 9 0 24 Jun 2022
PrivFairFL: Privacy-Preserving Group Fairness in Federated Learning Sikha Pentyala Nicola Neophytou A. Nascimento Martine De Cock G. Farnadi 26 17 0 23 May 2022
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 47 20 0 09 Nov 2021
Decentralized Wireless Federated Learning with Differential Privacy Shuzhen Chen Dongxiao Yu Yifei Zou Jiguo Yu Xiuzhen Cheng 35 48 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 36 51 0 17 Sep 2021
Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection Shulai Zhang Zirui Li Quan Chen Wenli Zheng Jingwen Leng M. Guo FedML 54 32 0 08 Sep 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 176 267 0 26 Feb 2021
CaPC Learning: Confidential and Private Collaborative Learning Christopher A. Choquette-Choo Natalie Dullerud Adam Dziedzic Yunxiang Zhang S. Jha Nicolas Papernot Xiao Wang FedML 59 57 0 09 Feb 2021
Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication Muah Kim Onur Gunlu Rafael F. Schaefer FedML 101 118 0 09 Feb 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 169 351 0 07 Dec 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 186 432 0 04 Mar 2020
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 141 1,680 0 14 Apr 2018