FedNL: Making Newton-Type Methods Applicable to Federated Learning

FedNL: Making Newton-Type Methods Applicable to Federated Learning

5 June 2021

Peter Richtárik

Papers citing "FedNL: Making Newton-Type Methods Applicable to Federated Learning"

18 / 18 papers shown

Title
Accelerated Distributed Optimization with Compression and Error Feedback Yuan Gao Anton Rodomanov Jeremy Rack Sebastian U. Stich 61 0 0 11 Mar 2025
Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis Zhijie Chen Qiaobo Li A. Banerjee FedML 42 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 60 0 0 08 Aug 2024
FAGH: Accelerating Federated Learning with Approximated Global Hessian Mrinmay Sen A. K. Qin Krishna Mohan FedML 45 0 0 16 Mar 2024
Matrix Compression via Randomized Low Rank and Low Precision Factorization R. Saha Varun Srivastava Mert Pilanci 36 20 0 17 Oct 2023
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates Ahmad Rammal Kaja Gruntkowska Nikita Fedin Eduard A. Gorbunov Peter Richtárik 58 5 0 15 Oct 2023
Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup Yan Sun Li Shen Hao Sun Liang Ding Dacheng Tao FedML 29 17 0 30 Jul 2023
Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization Nicolò Dal Fabbro M. Rossi Luca Schenato S. Dey 31 0 0 18 May 2023
Network-GIANT: Fully distributed Newton-type optimization via harmonic Hessian consensus A. Maritan Ganesh Sharma Luca Schenato S. Dey 38 2 0 13 May 2023
PersA-FL: Personalized Asynchronous Federated Learning Taha Toghani Soomin Lee César A. Uribe FedML 75 6 0 03 Oct 2022
Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with Inexact Prox Abdurakhmon Sadiev D. Kovalev Peter Richtárik 43 20 0 08 Jul 2022
FedSSO: A Federated Server-Side Second-Order Optimization Algorithm Xinteng Ma Renyi Bao Jinpeng Jiang Yang Liu Arthur Jiang Junhua Yan Xin Liu Zhisong Pan FedML 37 6 0 20 Jun 2022
Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation Rustem Islamov Xun Qian Slavomír Hanzely M. Safaryan Peter Richtárik 45 16 0 07 Jun 2022
Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence Sen Na Michal Derezinski Michael W. Mahoney 44 16 0 20 Apr 2022
SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing Nicolò Dal Fabbro S. Dey M. Rossi Luca Schenato FedML 67 14 0 11 Feb 2022
FL_PyTorch: optimization research simulator for federated learning Konstantin Burlachenko Samuel Horváth Peter Richtárik FedML 53 18 0 07 Feb 2022
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning Xun Qian Rustem Islamov M. Safaryan Peter Richtárik FedML 44 23 0 02 Nov 2021
Linearly Converging Error Compensated SGD Eduard A. Gorbunov D. Kovalev Dmitry Makarenko Peter Richtárik 166 78 0 23 Oct 2020