LocalNewton: Reducing Communication Bottleneck for Distributed Learning

16 May 2021

Papers citing "LocalNewton: Reducing Communication Bottleneck for Distributed Learning"

8 / 8 papers shown

Title
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning Z. Yao A. Gholami Sheng Shen Mustafa Mustafa Kurt Keutzer Michael W. Mahoney ODL 73 280 0 01 Jun 2020
Stochastic Weight Averaging in Parallel: Large-Batch Training that Generalizes Well Vipul Gupta S. Serrano D. DeCoste MoMe 56 58 0 07 Jan 2020
Serverless Computing: One Step Forward, Two Steps Back J. M. Hellerstein Jose M. Faleiro Joseph E. Gonzalez Johann Schleier-Smith Vikram Sreekanti Alexey Tumanov Chenggang Wu 27 390 0 10 Dec 2018
Local SGD Converges Fast and Communicates Little Sebastian U. Stich FedML 152 1,056 0 24 May 2018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 102 1,399 0 05 Dec 2017
CoCoA: A General Framework for Communication-Efficient Distributed Optimization Virginia Smith Simone Forte Chenxin Ma Martin Takáč Michael I. Jordan Martin Jaggi 49 272 0 07 Nov 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 269 4,620 0 18 Oct 2016
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 98 195 0 23 Jun 2015