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2202.05318
Cited By
Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning
10 February 2022
A. Bietti
Chen-Yu Wei
Miroslav Dudík
John Langford
Zhiwei Steven Wu
FedML
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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
^2
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
1