First Analysis of Local GD on Heterogeneous Data

10 September 2019

Ahmed Khaled

Konstantin Mishchenko

Peter Richtárik

FedML

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Papers citing "First Analysis of Local GD on Heterogeneous Data"

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Title
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning Nurbek Tastan Samuel Horváth Martin Takáč Karthik Nandakumar FedML 59 0 0 03 Oct 2024
Semi-Variance Reduction for Fair Federated Learning Saber Malekmohammadi Yaoliang Yu FedML 80 1 0 23 Jun 2024
Kimad: Adaptive Gradient Compression with Bandwidth Awareness Jihao Xin Ivan Ilin Shunkang Zhang Marco Canini Peter Richtárik 34 2 0 13 Dec 2023
Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup Yan Sun Li Shen Hao Sun Liang Ding Dacheng Tao FedML 24 17 0 30 Jul 2023
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation Davoud Ataee Tarzanagh Mingchen Li Pranay Sharma Samet Oymak 26 0 0 02 Jun 2023
Local SGD Accelerates Convergence by Exploiting Second Order Information of the Loss Function Linxuan Pan Shenghui Song FedML 25 2 0 24 May 2023
Federated TD Learning over Finite-Rate Erasure Channels: Linear Speedup under Markovian Sampling Nicolò Dal Fabbro A. Mitra George J. Pappas FedML 35 12 0 14 May 2023
Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity Han Wang A. Mitra Hamed Hassani George J. Pappas James Anderson FedML 29 21 0 04 Feb 2023
Communication-Efficient Local SGD with Age-Based Worker Selection Feng Zhu Jingjing Zhang Xin Wang 32 1 0 31 Oct 2022
GradSkip: Communication-Accelerated Local Gradient Methods with Better Computational Complexity A. Maranjyan M. Safaryan Peter Richtárik 34 13 0 28 Oct 2022
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability Zhao-quan Song Yitan Wang Zheng Yu Licheng Zhang FedML 23 28 0 15 Oct 2022
On the Performance of Gradient Tracking with Local Updates Edward Duc Hien Nguyen Sulaiman A. Alghunaim Kun Yuan César A. Uribe 40 19 0 10 Oct 2022
STSyn: Speeding Up Local SGD with Straggler-Tolerant Synchronization Feng Zhu Jingjing Zhang Xin Wang 33 3 0 06 Oct 2022
Multi-Level Branched Regularization for Federated Learning Jinkyu Kim Geeho Kim Bohyung Han FedML 22 53 0 14 Jul 2022
Federated Latent Class Regression for Hierarchical Data Bin Yang T. Carette Masanobu Jimbo Shinya Maruyama FedML 20 0 0 22 Jun 2022
Federated Random Reshuffling with Compression and Variance Reduction Grigory Malinovsky Peter Richtárik FedML 27 10 0 08 May 2022
FedNest: Federated Bilevel, Minimax, and Compositional Optimization Davoud Ataee Tarzanagh Mingchen Li Christos Thrampoulidis Samet Oymak FedML 42 73 0 04 May 2022
Understanding A Class of Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective Xinwei Zhang Mingyi Hong N. Elia FedML 15 3 0 27 Apr 2022
Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients Riccardo Zaccone Andrea Rizzardi Debora Caldarola Marco Ciccone Barbara Caputo FedML 58 14 0 26 Jan 2022
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi Ma Zhao-quan Song Guang Lin FedML 30 16 0 09 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 43 16 0 05 Dec 2021
Federated Semi-Supervised Learning with Class Distribution Mismatch Zhiguo Wang Xintong Wang Ruoyu Sun Tsung-Hui Chang FedML 21 12 0 29 Oct 2021
A Stochastic Newton Algorithm for Distributed Convex Optimization Brian Bullins Kumar Kshitij Patel Ohad Shamir Nathan Srebro Blake E. Woodworth 28 15 0 07 Oct 2021
Cost-Effective Federated Learning in Mobile Edge Networks Bing Luo Xiang Li Shiqiang Wang Jianwei Huang Leandros Tassiulas FedML 57 72 0 12 Sep 2021
Iterated Vector Fields and Conservatism, with Applications to Federated Learning Zachary B. Charles Keith Rush 27 6 0 08 Sep 2021
An Operator Splitting View of Federated Learning Saber Malekmohammadi K. Shaloudegi Zeou Hu Yaoliang Yu FedML 26 2 0 12 Aug 2021
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy Xinwei Zhang Xiangyi Chen Min-Fong Hong Zhiwei Steven Wu Jinfeng Yi FedML 30 91 0 25 Jun 2021
On Large-Cohort Training for Federated Learning Zachary B. Charles Zachary Garrett Zhouyuan Huo Sergei Shmulyian Virginia Smith FedML 21 113 0 15 Jun 2021
Decentralized Federated Averaging Tao Sun Dongsheng Li Bao Wang FedML 48 207 0 23 Apr 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
Vertical federated learning based on DFP and BFGS Wenjie Song Xuan Shen FedML 19 6 0 23 Jan 2021
Federated Learning under Importance Sampling Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 16 52 0 14 Dec 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 32 0 0 26 Aug 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 16 1,297 0 15 Jul 2020
Minibatch vs Local SGD for Heterogeneous Distributed Learning Blake E. Woodworth Kumar Kshitij Patel Nathan Srebro FedML 22 199 0 08 Jun 2020
FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Data Xinwei Zhang Mingyi Hong S. Dhople W. Yin Yang Liu FedML 21 227 0 22 May 2020
Adaptive Federated Optimization Sashank J. Reddi Zachary B. Charles Manzil Zaheer Zachary Garrett Keith Rush Jakub Konecný Sanjiv Kumar H. B. McMahan FedML 20 1,391 0 29 Feb 2020
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization Zhize Li D. Kovalev Xun Qian Peter Richtárik FedML AI4CE 26 133 0 26 Feb 2020
Dynamic Federated Learning Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 22 25 0 20 Feb 2020
Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability Yikai Yan Chaoyue Niu Yucheng Ding Zhenzhe Zheng Fan Wu Guihai Chen Shaojie Tang Zhihua Wu FedML 49 37 0 18 Feb 2020
On the Convergence of Local Descent Methods in Federated Learning Farzin Haddadpour M. Mahdavi FedML 19 266 0 31 Oct 2019
Gradient Descent with Compressed Iterates Ahmed Khaled Peter Richtárik 21 22 0 10 Sep 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 64 2,283 0 04 Jul 2019
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 144 1,687 0 14 Apr 2018