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Understanding Clipping for Federated Learning: Convergence and
  Client-Level Differential Privacy

Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy

25 June 2021
Xinwei Zhang
Xiangyi Chen
Min-Fong Hong
Zhiwei Steven Wu
Jinfeng Yi
    FedML
ArXivPDFHTML

Papers citing "Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy"

13 / 13 papers shown
Title
DC-SGD: Differentially Private SGD with Dynamic Clipping through Gradient Norm Distribution Estimation
DC-SGD: Differentially Private SGD with Dynamic Clipping through Gradient Norm Distribution Estimation
Chengkun Wei
Weixian Li
Chen Gong
Wenzhi Chen
53
0
0
29 Mar 2025
Biased Federated Learning under Wireless Heterogeneity
Muhammad Faraz Ul Abrar
Nicolò Michelusi
FedML
44
0
0
08 Mar 2025
Controlled privacy leakage propagation throughout overlapping grouped learning
Shahrzad Kiani
Franziska Boenisch
S. Draper
FedML
72
0
0
06 Mar 2025
Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees
Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees
Aleksandar Armacki
Shuhua Yu
Pranay Sharma
Gauri Joshi
Dragana Bajović
D. Jakovetić
S. Kar
55
2
0
17 Oct 2024
Layered Randomized Quantization for Communication-Efficient and
  Privacy-Preserving Distributed Learning
Layered Randomized Quantization for Communication-Efficient and Privacy-Preserving Distributed Learning
Guangfeng Yan
Tan Li
Tian-Shing Lan
Kui Wu
Linqi Song
19
6
0
12 Dec 2023
PCDP-SGD: Improving the Convergence of Differentially Private SGD via Projection in Advance
PCDP-SGD: Improving the Convergence of Differentially Private SGD via Projection in Advance
Haichao Sha
Ruixuan Liu
Yi-xiao Liu
Hong Chen
41
1
0
06 Dec 2023
Using Decentralized Aggregation for Federated Learning with Differential
  Privacy
Using Decentralized Aggregation for Federated Learning with Differential Privacy
H. Saleh
Y. El-Sonbaty
Ana Fernández Vilas
M. Fernández-Veiga
Nashwa El-Bendary
FedML
17
3
0
27 Nov 2023
Heterogeneous Federated Learning: State-of-the-art and Research
  Challenges
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
Clip21: Error Feedback for Gradient Clipping
Clip21: Error Feedback for Gradient Clipping
Sarit Khirirat
Eduard A. Gorbunov
Samuel Horváth
Rustem Islamov
Fakhri Karray
Peter Richtárik
25
10
0
30 May 2023
Convergence and Privacy of Decentralized Nonconvex Optimization with
  Gradient Clipping and Communication Compression
Convergence and Privacy of Decentralized Nonconvex Optimization with Gradient Clipping and Communication Compression
Boyue Li
Yuejie Chi
21
12
0
17 May 2023
U-Clip: On-Average Unbiased Stochastic Gradient Clipping
U-Clip: On-Average Unbiased Stochastic Gradient Clipping
Bryn Elesedy
Marcus Hutter
11
1
0
06 Feb 2023
Beyond Uniform Lipschitz Condition in Differentially Private
  Optimization
Beyond Uniform Lipschitz Condition in Differentially Private Optimization
Rudrajit Das
Satyen Kale
Zheng Xu
Tong Zhang
Sujay Sanghavi
22
17
0
21 Jun 2022
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
Xinjian Luo
Xiangqi Zhu
FedML
60
25
0
27 Apr 2020
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