EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback

9 June 2021

Papers citing "EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback"

25 / 25 papers shown

Title
Convergence Analysis of Asynchronous Federated Learning with Gradient Compression for Non-Convex Optimization Diying Yang Yingwei Hou Danyang Xiao Weigang Wu FedML 34 0 0 28 Apr 2025
Striving for Simplicity: Simple Yet Effective Prior-Aware Pseudo-Labeling for Semi-Supervised Ultrasound Image Segmentation Yaxiong Chen Yujie Wang Zixuan Zheng Jingliang Hu Yilei Shi Shengwu Xiong Xiao Xiang Zhu Lichao Mou 52 0 0 18 Mar 2025
Accelerated Distributed Optimization with Compression and Error Feedback Yuan Gao Anton Rodomanov Jeremy Rack Sebastian U. Stich 43 0 0 11 Mar 2025
Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis Zhijie Chen Qiaobo Li A. Banerjee FedML 28 0 0 11 Nov 2024
Federated Cubic Regularized Newton Learning with Sparsification-amplified Differential Privacy Wei Huo Changxin Liu Kemi Ding Karl H. Johansson Ling Shi FedML 30 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
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression Laurent Condat A. Maranjyan Peter Richtárik 34 3 0 07 Mar 2024
Correlated Quantization for Faster Nonconvex Distributed Optimization Andrei Panferov Yury Demidovich Ahmad Rammal Peter Richtárik MQ 23 4 0 10 Jan 2024
Kimad: Adaptive Gradient Compression with Bandwidth Awareness Jihao Xin Ivan Ilin Shunkang Zhang Marco Canini Peter Richtárik 28 2 0 13 Dec 2023
Federated Learning is Better with Non-Homomorphic Encryption Konstantin Burlachenko Abdulmajeed Alrowithi Fahad Ali Albalawi Peter Richtárik FedML 22 6 0 04 Dec 2023
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates Ahmad Rammal Kaja Gruntkowska Nikita Fedin Eduard A. Gorbunov Peter Richtárik 32 5 0 15 Oct 2023
Asynchronous Federated Learning with Bidirectional Quantized Communications and Buffered Aggregation Tomàs Ortega Hamid Jafarkhani FedML 19 6 0 01 Aug 2023
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
Error Feedback Shines when Features are Rare Peter Richtárik Elnur Gasanov Konstantin Burlachenko 13 2 0 24 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
Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression Yutong He Xinmeng Huang Yiming Chen W. Yin Kun Yuan 26 7 0 12 May 2023
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features Aleksandr Beznosikov David Dobre Gauthier Gidel 18 5 0 23 Apr 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 21 6 0 08 Mar 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities Aleksandr Beznosikov Martin Takáč Alexander Gasnikov 21 10 0 15 Feb 2023
CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence Kun-Yen Huang Shin-Yi Pu 19 9 0 14 Jan 2023
Adaptive Compression for Communication-Efficient Distributed Training Maksim Makarenko Elnur Gasanov Rustem Islamov Abdurakhmon Sadiev Peter Richtárik 10 12 0 31 Oct 2022
High Probability Bounds for Stochastic Subgradient Schemes with Heavy Tailed Noise D. A. Parletta Andrea Paudice Massimiliano Pontil Saverio Salzo 26 9 0 17 Aug 2022
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods Aleksandr Beznosikov Eduard A. Gorbunov Hugo Berard Nicolas Loizou 17 47 0 15 Feb 2022
Linearly Converging Error Compensated SGD Eduard A. Gorbunov D. Kovalev Dmitry Makarenko Peter Richtárik 163 77 0 23 Oct 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 12 124 0 25 Aug 2020