Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning

10 February 2022

Papers citing "Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning"

26 / 26 papers shown

Title
Personalized Federated Training of Diffusion Models with Privacy Guarantees Kumar Kshitij Patel Weitong Zhang Lingxiao Wang MedIm 47 0 0 01 Apr 2025
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
Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates Chuanyin Wang Yifei Zhang Neng Gao Qiang Luo FedML 60 0 0 12 Mar 2025
FedTLU: Federated Learning with Targeted Layer Updates Jong-Ik Park Carlee Joe-Wong FedML 84 0 0 28 Jan 2025
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients Youssef Allouah Abdellah El Mrini R. Guerraoui Nirupam Gupta Rafael Pinot FedML 25 0 0 30 Sep 2024
DP $^2$ -FedSAM: Enhancing Differentially Private Federated Learning Through Personalized Sharpness-Aware Minimization Zhenxiao Zhang Yuanxiong Guo Yanmin Gong FedML 28 0 0 20 Sep 2024
Semi-Variance Reduction for Fair Federated Learning Saber Malekmohammadi Yaoliang Yu FedML 70 1 0 23 Jun 2024
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates Youssef Allouah Sadegh Farhadkhani R. Guerraoui Nirupam Gupta Rafael Pinot Geovani Rizk S. Voitovych FedML 22 4 0 20 Feb 2024
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off Yuecheng Li Lele Fu Tong Wang Jian Lou Bin Chen Lei Yang Zibin Zheng Zibin Zheng Chuan Chen FedML 65 4 0 10 Feb 2024
Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning Kangkang Sun Xiaojin Zhang Xi Lin Gaolei Li Jing Wang Jianhua Li 27 4 0 30 Nov 2023
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning Zebang Shen Jiayuan Ye Anmin Kang Hamed Hassani Reza Shokri FedML 24 16 0 11 Sep 2023
Collaborative Learning From Distributed Data With Differentially Private Synthetic Twin Data Lukas Prediger Joonas Jälkö Antti Honkela Samuel Kaski FedML 19 1 0 09 Aug 2023
Heterogeneous Federated Learning: State-of-the-art and Research Challenges Mang Ye Xiuwen Fang Bo Du PongChi Yuen Dacheng Tao FedML AAML 29 244 0 20 Jul 2023
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning Zachary B. Charles Nicole Mitchell Krishna Pillutla Michael Reneer Zachary Garrett FedML AI4CE 23 28 0 18 Jul 2023
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation Zhanke Zhou Chenyu Zhou Xuan Li Jiangchao Yao Quanming Yao Bo Han AAML 37 17 0 15 Jun 2023
Balancing Privacy Protection and Interpretability in Federated Learning Zhe Li Honglong Chen Zhichen Ni Huajie Shao FedML 8 8 0 16 Feb 2023
Federated Learning with Heterogeneous Differential Privacy Nasser Aldaghri Hessam Mahdavifar Ahmad Beirami FedML 16 2 0 28 Oct 2021
Private Multi-Task Learning: Formulation and Applications to Federated Learning Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 13 19 0 30 Aug 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 173 410 0 14 Jul 2021
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning Shaoxiong Ji Yue Tan Teemu Saravirta Zhiqin Yang Yixin Liu Lauri Vasankari Shirui Pan Guodong Long A. Walid FedML 21 76 0 25 Feb 2021
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications Matthias Paulik M. Seigel Henry Mason Dominic Telaar Joris Kluivers ... Dominic Hughes O. Javidbakht Fei Dong Rehan Rishi Stanley Hung FedML 175 126 0 16 Feb 2021
Adaptive Personalized Federated Learning Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 183 541 0 30 Mar 2020
Device Heterogeneity in Federated Learning: A Superquantile Approach Yassine Laguel Krishna Pillutla J. Malick Zaïd Harchaoui FedML 19 22 0 25 Feb 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 243 11,659 0 09 Mar 2017
Mechanism Design in Large Games: Incentives and Privacy Michael Kearns Mallesh M. Pai Aaron Roth Jonathan R. Ullman 77 182 0 17 Jul 2012
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 166 683 0 07 Dec 2010