Models of fairness in federated learning

1 December 2021

Papers citing "Models of fairness in federated learning"

27 / 27 papers shown

Title
The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning Justin Singh Kang Ramtin Pedarsani Kannan Ramchandran FedML 65 5 0 30 Jan 2023
Differentially Private Federated Clustering over Non-IID Data Yiwei Li Shuai Wang Chong-Yung Chi Tony Q.S. Quek FedML 54 13 0 03 Jan 2023
Fairness in Federated Learning via Core-Stability Bhaskar Chaudhury Linyi Li Mintong Kang Yue Liu R. Mehta FedML 43 32 0 03 Nov 2022
Private Estimation with Public Data Alex Bie Gautam Kamath Vikrant Singhal 49 31 0 16 Aug 2022
Mechanisms that Incentivize Data Sharing in Federated Learning Sai Praneeth Karimireddy Wenshuo Guo Michael I. Jordan FedML 63 49 0 10 Jul 2022
Motley: Benchmarking Heterogeneity and Personalization in Federated Learning Shan-shan Wu Tian Li Zachary B. Charles Yu Xiao Ziyu Liu Zheng Xu Virginia Smith FedML 77 45 0 18 Jun 2022
When the Curious Abandon Honesty: Federated Learning Is Not Private Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 91 184 0 06 Dec 2021
Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspective Xuezhen Tu Kun Zhu Nguyen Cong Luong Dusit Niyato Yang Zhang Juan Li FedML AI4CE 65 120 0 20 Nov 2021
Unified Group Fairness on Federated Learning Fengda Zhang Kun Kuang Yuxuan Liu Long Chen Chao-Xiang Wu Leilei Gan Jiaxun Lu Yunfeng Shao Jun Xiao FedML 96 20 0 09 Nov 2021
Improving Fairness via Federated Learning Yuchen Zeng Hongxu Chen Kangwook Lee FedML 55 63 0 29 Oct 2021
Optimal Model Averaging: Towards Personalized Collaborative Learning Felix Grimberg Mary-Anne Hartley Sai Praneeth Karimireddy Martin Jaggi FedML MoMe 40 15 0 25 Oct 2021
Federating for Learning Group Fair Models Afroditi Papadaki Natalia Martínez Martín Bertrán Guillermo Sapiro Miguel R. D. Rodrigues FedML FaML 57 17 0 05 Oct 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 65 48 0 19 Sep 2021
Optimality and Stability in Federated Learning: A Game-theoretic Approach Kate Donahue Jon M. Kleinberg FedML 50 47 0 17 Jun 2021
Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data Esther Rolf Theodora Worledge Benjamin Recht Michael I. Jordan 54 32 0 05 Mar 2021
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning Avrim Blum Nika Haghtalab R. L. Phillips Han Shao FedML 43 49 0 04 Mar 2021
Mitigating Bias in Federated Learning Annie Abay Yi Zhou Nathalie Baracaldo Shashank Rajamoni Ebube Chuba Heiko Ludwig AI4CE 37 91 0 04 Dec 2020
Fairness-aware Agnostic Federated Learning Wei Du Depeng Xu Xintao Wu Hanghang Tong FedML 57 130 0 10 Oct 2020
Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation Kate Donahue Jon M. Kleinberg FedML 46 80 0 02 Oct 2020
Collaborative Fairness in Federated Learning Lingjuan Lyu Xinyi Xu Qian Wang FedML 68 192 0 27 Aug 2020
Hierarchically Fair Federated Learning Jingfeng Zhang Cheng Li A. Robles-Kelly Mohan Kankanhalli FedML 37 56 0 22 Apr 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 176 6,229 0 10 Dec 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 105 4,496 0 21 Aug 2019
Fair Resource Allocation in Federated Learning Tian Li Maziar Sanjabi Ahmad Beirami Virginia Smith FedML 144 798 0 25 May 2019
Agnostic Federated Learning M. Mohri Gary Sivek A. Suresh FedML 117 932 0 01 Feb 2019
Deep Learning Scaling is Predictable, Empirically Joel Hestness Sharan Narang Newsha Ardalani G. Diamos Heewoo Jun Hassan Kianinejad Md. Mostofa Ali Patwary Yang Yang Yanqi Zhou 87 736 0 01 Dec 2017
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 327 17,399 0 17 Feb 2016