Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization

26 February 2020

Papers citing "Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization"

29 / 29 papers shown

Title
LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression Laurent Condat A. Maranjyan Peter Richtárik 39 3 0 07 Mar 2024
Correlated Quantization for Faster Nonconvex Distributed Optimization Andrei Panferov Yury Demidovich Ahmad Rammal Peter Richtárik MQ 28 4 0 10 Jan 2024
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates Ahmad Rammal Kaja Gruntkowska Nikita Fedin Eduard A. Gorbunov Peter Richtárik 37 5 0 15 Oct 2023
Error Feedback Shines when Features are Rare Peter Richtárik Elnur Gasanov Konstantin Burlachenko 23 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
Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$ -Means Clustering Lingxiao Huang Zhize Li Jialin Sun Haoyu Zhao FedML 31 9 0 26 Oct 2022
lo-fi: distributed fine-tuning without communication Mitchell Wortsman Suchin Gururangan Shen Li Ali Farhadi Ludwig Schmidt Michael G. Rabbat Ari S. Morcos 27 24 0 19 Oct 2022
Accelerated Federated Learning with Decoupled Adaptive Optimization Jiayin Jin Jiaxiang Ren Yang Zhou Lingjuan Lyu Ji Liu Dejing Dou AI4CE FedML 19 51 0 14 Jul 2022
Linear Stochastic Bandits over a Bit-Constrained Channel A. Mitra Hamed Hassani George J. Pappas 34 8 0 02 Mar 2022
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods Aleksandr Beznosikov Eduard A. Gorbunov Hugo Berard Nicolas Loizou 19 47 0 15 Feb 2022
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression Haoyu Zhao Boyue Li Zhize Li Peter Richtárik Yuejie Chi 19 48 0 31 Jan 2022
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning Xun Qian Rustem Islamov M. Safaryan Peter Richtárik FedML 19 23 0 02 Nov 2021
An Operator Splitting View of Federated Learning Saber Malekmohammadi K. Shaloudegi Zeou Hu Yaoliang Yu FedML 24 2 0 12 Aug 2021
Vertical Federated Learning without Revealing Intersection Membership Jiankai Sun Xin Yang Yuanshun Yao Aonan Zhang Weihao Gao Junyuan Xie Chong-Jun Wang FedML 23 37 0 10 Jun 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning M. Safaryan Rustem Islamov Xun Qian Peter Richtárik FedML 20 77 0 05 Jun 2021
EasyFL: A Low-code Federated Learning Platform For Dummies Weiming Zhuang Xin Gan Yonggang Wen Shuai Zhang FedML 19 46 0 17 May 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method Zhize Li 33 14 0 21 Mar 2021
Personalized Federated Learning using Hypernetworks Aviv Shamsian Aviv Navon Ethan Fetaya Gal Chechik FedML 25 324 0 08 Mar 2021
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices Max Ryabinin Eduard A. Gorbunov Vsevolod Plokhotnyuk Gennady Pekhimenko 29 31 0 04 Mar 2021
Distributed Second Order Methods with Fast Rates and Compressed Communication Rustem Islamov Xun Qian Peter Richtárik 21 51 0 14 Feb 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
Federated Learning with Nesterov Accelerated Gradient Zhengjie Yang Wei Bao Dong Yuan Nguyen H. Tran Albert Y. Zomaya FedML 19 29 0 18 Sep 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 24 125 0 25 Aug 2020
Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications Jihong Park S. Samarakoon Anis Elgabli Joongheon Kim M. Bennis Seong-Lyun Kim Mérouane Debbah 25 161 0 06 Aug 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 14 1,295 0 15 Jul 2020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees Farzin Haddadpour Mohammad Mahdi Kamani Aryan Mokhtari M. Mahdavi FedML 25 271 0 02 Jul 2020
Detached Error Feedback for Distributed SGD with Random Sparsification An Xu Heng-Chiao Huang 33 9 0 11 Apr 2020
Personalized Federated Learning: A Meta-Learning Approach Alireza Fallah Aryan Mokhtari Asuman Ozdaglar FedML 31 560 0 19 Feb 2020
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning Anis Elgabli Jihong Park Amrit Singh Bedi Chaouki Ben Issaid M. Bennis Vaneet Aggarwal 16 67 0 23 Oct 2019