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

Zhiwei Steven Wu

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

16 / 16 papers shown

Title
DC-SGD: Differentially Private SGD with Dynamic Clipping through Gradient Norm Distribution Estimation Chengkun Wei Weixian Li Chen Gong Wenzhi Chen 58 0 0 29 Mar 2025
Biased Federated Learning under Wireless Heterogeneity Muhammad Faraz Ul Abrar Nicolò Michelusi FedML 46 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 Aleksandar Armacki Shuhua Yu Pranay Sharma Gauri Joshi Dragana Bajović D. Jakovetić S. Kar 57 2 0 17 Oct 2024
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 Haichao Sha Ruixuan Liu Yi-xiao Liu Hong Chen 52 1 0 06 Dec 2023
Using Decentralized Aggregation for Federated Learning with Differential Privacy H. Saleh Y. El-Sonbaty Ana Fernández Vilas M. Fernández-Veiga Nashwa El-Bendary FedML 24 3 0 27 Nov 2023
Heterogeneous Federated Learning: State-of-the-art and Research Challenges Mang Ye Xiuwen Fang Bo Du PongChi Yuen Dacheng Tao FedML AAML 39 244 0 20 Jul 2023
Clip21: Error Feedback for Gradient Clipping Sarit Khirirat Eduard A. Gorbunov Samuel Horváth Rustem Islamov Fakhri Karray Peter Richtárik 32 10 0 30 May 2023
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 Bryn Elesedy Marcus Hutter 19 1 0 06 Feb 2023
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 32 2 0 28 Oct 2022
Taming Fat-Tailed ("Heavier-Tailed'' with Potentially Infinite Variance) Noise in Federated Learning Haibo Yang Pei-Yuan Qiu Jia Liu FedML 27 12 0 03 Oct 2022
Beyond Uniform Lipschitz Condition in Differentially Private Optimization Rudrajit Das Satyen Kale Zheng Xu Tong Zhang Sujay Sanghavi 24 17 0 21 Jun 2022
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 37 76 0 25 Feb 2021
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning Xinjian Luo Xiangqi Zhu FedML 73 25 0 27 Apr 2020