Towards Fairness-Aware Federated Learning

2 November 2021

Papers citing "Towards Fairness-Aware Federated Learning"

37 / 37 papers shown

Title
Towards Unbiased Federated Graph Learning: Label and Topology Perspectives Zhengyu Wu Boyang Pang Xunkai Li Y. X. Zhu Daohan Su Bowen Fan R. Li Guoren Wang Chenghu Zhou FedML 33 0 0 14 Apr 2025
pFedFair: Towards Optimal Group Fairness-Accuracy Trade-off in Heterogeneous Federated Learning Haoyu Lei Shizhan Gong Qi Dou Farzan Farnia FedML 59 0 0 19 Mar 2025
FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Prediction Siqi Li Qiming Wu Xin Li Di Miao Chuan Hong ... Michael Hao Chen Mengying Yan Yilin Ning M. Ong Nan Liu 26 1 0 07 Oct 2024
Federated Fairness Analytics: Quantifying Fairness in Federated Learning Oscar Dilley Juan Marcelo Parra Ullauri Rasheed Hussain Dimitra Simeonidou FedML 34 0 0 15 Aug 2024
Addressing Skewed Heterogeneity via Federated Prototype Rectification with Personalization Shunxin Guo Hongsong Wang Shuxia Lin Zhiqiang Kou Xin Geng FedML 33 1 0 15 Aug 2024
Heterogeneity: An Open Challenge for Federated On-board Machine Learning Maria Hartmann Grégoire Danoy Pascal Bouvry FedML 26 0 0 13 Aug 2024
Enhancing Group Fairness in Federated Learning through Personalization Yifan Yang Ali Payani Parinaz Naghizadeh Ardabili FedML 32 0 0 27 Jul 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 27 1 0 01 Jun 2024
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 38 1 0 31 May 2024
Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity Yuhang Chen Wenke Huang Mang Ye FedML 38 16 0 26 May 2024
Advances and Open Challenges in Federated Learning with Foundation Models Chao Ren Han Yu Hongyi Peng Xiaoli Tang Anran Li ... A. Tan Bo Zhao Xiaoxiao Li Zengxiang Li Qiang Yang FedML AIFin AI4CE 68 6 0 23 Apr 2024
HeteroSwitch: Characterizing and Taming System-Induced Data Heterogeneity in Federated Learning Gyudong Kim Mehdi Ghasemi Soroush Heidari Seungryong Kim Young Geun Kim S. Vrudhula Carole-Jean Wu 27 1 0 07 Mar 2024
A Bargaining-based Approach for Feature Trading in Vertical Federated Learning Yue Cui Liuyi Yao Zitao Li Yaliang Li Bolin Ding Xiaofang Zhou FedML 38 1 0 23 Feb 2024
Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learning Teresa Salazar Joao Gama Helder Araújo Pedro Abreu FaML FedML 29 2 0 12 Feb 2024
Federated Unlearning: a Perspective of Stability and Fairness Jiaqi Shao Tao Lin Xuanyu Cao Bing Luo MU 23 7 0 02 Feb 2024
An Auction-based Marketplace for Model Trading in Federated Learning Yue Cui Liuyi Yao Yaliang Li Ziqian Chen Bolin Ding Xiaofang Zhou FedML 32 3 0 02 Feb 2024
Distributed client selection with multi-objective in federated learning assisted Internet of Vehicles Narisu Cha Long Chang 25 0 0 06 Jan 2024
Fairness-Aware Job Scheduling for Multi-Job Federated Learning Yuxin Shi Han Yu FedML 20 3 0 05 Jan 2024
pFedES: Model Heterogeneous Personalized Federated Learning with Feature Extractor Sharing Liping Yi Han Yu Gang Wang Xiaoguang Liu 35 7 0 12 Nov 2023
Hire When You Need to: Gradual Participant Recruitment for Auction-based Federated Learning Xavier Tan Han Yu FedML 25 3 0 04 Oct 2023
A Survey on Image-text Multimodal Models Ruifeng Guo Jingxuan Wei Linzhuang Sun Khai Le-Duc Guiyong Chang Dawei Liu Sibo Zhang Zhengbing Yao Mingjun Xu Liping Bu VLM 21 5 0 23 Sep 2023
Fairness and Privacy in Federated Learning and Their Implications in Healthcare Navya Annapareddy Jade F. Preston Judy Fox FedML 16 3 0 15 Aug 2023
Towards Fair and Privacy Preserving Federated Learning for the Healthcare Domain Navya Annapareddy Yingzheng Liu Judy Fox OOD 9 2 0 03 Aug 2023
Fairness-Aware Client Selection for Federated Learning Yuxin Shi Zelei Liu Zhuan Shi Han Yu FedML 11 19 0 20 Jul 2023
Hierarchical Federated Learning Incentivization for Gas Usage Estimation Has Sun Xiaoli Tang Che-Sheng Yang Zhenpeng Yu Xiuli Wang Qijie Ding Zengxiang Li Han Yu FedML 22 1 0 01 Jul 2023
Fairness and Privacy-Preserving in Federated Learning: A Survey Taki Hasan Rafi Faiza Anan Noor Tahmid Hussain Dong-Kyu Chae FedML 35 39 0 14 Jun 2023
A Framework for Incentivized Collaborative Learning Xinran Wang Qi Le Ahmad Faraz Khan Jie Ding A. Anwar FedML 33 4 0 26 May 2023
Trustworthy Federated Learning: A Survey A. Tariq M. Serhani F. Sallabi Tariq Qayyum E. Barka K. Shuaib FedML 25 9 0 19 May 2023
Utility-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning Xiaoli Tang Han Yu FedML 16 17 0 11 May 2023
FedGH: Heterogeneous Federated Learning with Generalized Global Header Liping Yi Gang Wang Xiaoguang Liu Zhuan Shi Han Yu FedML 24 71 0 23 Mar 2023
Client Selection for Generalization in Accelerated Federated Learning: A Multi-Armed Bandit Approach Dan Ben Ami Kobi Cohen Qing Zhao FedML 19 11 0 18 Mar 2023
Efficient Training of Large-scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout Yuanyuan Chen Zichen Chen Sheng Guo Yansong Zhao Zelei Liu Pengcheng Wu Che-Sheng Yang Zengxiang Li Han Yu AI4CE 17 9 0 22 Feb 2023
A Snapshot of the Frontiers of Client Selection in Federated Learning Gergely Németh M. Lozano Novi Quadrianto Nuria Oliver FedML 94 14 0 27 Sep 2022
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 183 840 0 01 Mar 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
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 186 433 0 04 Mar 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,203 0 23 Aug 2019