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2003.10637
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FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection
24 March 2020
Ruixuan Liu
Yang Cao
Masatoshi Yoshikawa
Hong Chen
FedML
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Papers citing
"FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection"
21 / 21 papers shown
Title
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling
Shaowei Wang
Changyu Dong
Xiangfu Song
Jin Li
Zhili Zhou
Di Wang
Han Wu
114
0
0
26 Jun 2024
Training Machine Learning models at the Edge: A Survey
Aymen Rayane Khouas
Mohamed Reda Bouadjenek
Hakim Hacid
Sunil Aryal
111
12
0
05 Mar 2024
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks
Natalie Lang
Nir Shlezinger
Rafael G. L. DÓliveira
S. E. Rouayheb
FedML
156
4
0
01 Aug 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy
Yifei Zhang
Dun Zeng
Jinglong Luo
Zenglin Xu
Irwin King
FedML
156
49
0
21 Feb 2023
DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder
Bjarne Pfitzner
B. Arnrich
FedML
84
18
0
21 Nov 2022
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy
Zhifeng Jiang
Wei Wang
Ruichuan Chen
76
7
0
26 Sep 2022
FedPerm: Private and Robust Federated Learning by Parameter Permutation
Hamid Mozaffari
Virendra J. Marathe
D. Dice
FedML
80
4
0
16 Aug 2022
Measuring Lower Bounds of Local Differential Privacy via Adversary Instantiations in Federated Learning
Marin Matsumoto
Tsubasa Takahashi
Seng Pei Liew
M. Oguchi
FedML
BDL
50
0
0
18 Jun 2022
Federated Learning with Sparsified Model Perturbation: Improving Accuracy under Client-Level Differential Privacy
Rui Hu
Yanmin Gong
Yuanxiong Guo
FedML
87
72
0
15 Feb 2022
Improving Differentially Private SGD via Randomly Sparsified Gradients
Junyi Zhu
Matthew B. Blaschko
63
5
0
01 Dec 2021
Graph-Fraudster: Adversarial Attacks on Graph Neural Network Based Vertical Federated Learning
Jinyin Chen
Guohan Huang
Haibin Zheng
Shanqing Yu
Wenrong Jiang
Chen Cui
AAML
FedML
130
32
0
13 Oct 2021
Lightweight Transformer in Federated Setting for Human Activity Recognition
Ali Raza
K. Tran
L. Koehl
Shujun Li
Xianyi Zeng
Khaled Benzaidi
MedIm
72
10
0
01 Oct 2021
Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy
Yipeng Zhou
Xuezheng Liu
Yao Fu
Di Wu
Chao Li
Shui Yu
FedML
66
2
0
05 Jul 2021
Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback
Lorenzo Minto
Moritz Haller
Hamed Haddadi
B. Livshits
FedML
67
74
0
09 May 2021
From Distributed Machine Learning to Federated Learning: A Survey
Ji Liu
Jizhou Huang
Yang Zhou
Xuhong Li
Shilei Ji
Haoyi Xiong
Dejing Dou
FedML
OOD
140
259
0
29 Apr 2021
Federated Learning with Local Differential Privacy: Trade-offs between Privacy, Utility, and Communication
Muah Kim
Onur Gunlu
Rafael F. Schaefer
FedML
168
121
0
09 Feb 2021
Transparent Contribution Evaluation for Secure Federated Learning on Blockchain
Shuaicheng Ma
Yang Cao
L. Xiong
FedML
67
37
0
26 Jan 2021
On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times
Yao Fu
Yipeng Zhou
Di Wu
Shui Yu
Yonggang Wen
Chao Li
FedML
51
10
0
11 Jan 2021
A Comprehensive Survey on Local Differential Privacy Toward Data Statistics and Analysis
Teng Wang
Xuefeng Zhang
Xuefeng Zhang
Xinyu Yang
96
88
0
11 Oct 2020
FLAME: Differentially Private Federated Learning in the Shuffle Model
Ruixuan Liu
Yang Cao
Hong Chen
Ruoyang Guo
Masatoshi Yoshikawa
FedML
90
96
0
17 Sep 2020
Privacy-Preserving Classification with Secret Vector Machines
Valentin Hartmann
Konark Modi
J. M. Pujol
Robert West
74
14
0
08 Jul 2019
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