SoteriaFL: A Unified Framework for Private Federated Learning with
Communication Compression

SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression

20 June 2022

Papers citing "SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression"

12 / 12 papers shown

Title
Dyn-D $^2$ P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee Z. Zhu Y. Huang Xin Wang Shouling Ji Jinming Xu 26 0 0 10 May 2025
Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy Wei Huo Changxin Liu Kemi Ding Karl H. Johansson Ling Shi FedML 35 0 0 08 Aug 2024
Communication-efficient Vertical Federated Learning via Compressed Error Feedback Pedro Valdeira João Xavier Cláudia Soares Yuejie Chi FedML 30 4 0 20 Jun 2024
PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds Zehan Zhu Yan Huang Xin Wang Jinming Xu 37 0 0 04 May 2024
A Survey for Federated Learning Evaluations: Goals and Measures Di Chai Leye Wang Liu Yang Junxue Zhang Kai Chen Qian Yang ELM FedML 17 21 0 23 Aug 2023
Convergence and Privacy of Decentralized Nonconvex Optimization with Gradient Clipping and Communication Compression Boyue Li Yuejie Chi 21 12 0 17 May 2023
Distributed Learning Meets 6G: A Communication and Computing Perspective Shashank Jere Yifei Song Y. Yi Lingjia Liu 16 10 0 02 Mar 2023
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression Haoyu Zhao Boyue Li Zhize Li Peter Richtárik Yuejie Chi 17 48 0 31 Jan 2022
EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback Ilyas Fatkhullin Igor Sokolov Eduard A. Gorbunov Zhize Li Peter Richtárik 44 44 0 07 Oct 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 173 411 0 14 Jul 2021
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 55 157 0 14 Feb 2021
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 157 760 0 28 Sep 2019