One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them

12 May 2019

Papers citing "One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them"

9 / 9 papers shown

Title
Order Optimal One-Shot Distributed Learning Arsalan Sharifnassab Saber Salehkaleybar S. J. Golestani 32 10 0 02 Nov 2019
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 390 17,453 0 17 Feb 2016
Federated Optimization:Distributed Optimization Beyond the Datacenter Jakub Konecný H. B. McMahan Daniel Ramage FedML 113 737 0 11 Nov 2015
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization Xiangru Lian Yijun Huang Y. Li Ji Liu 135 499 0 27 Jun 2015
Communication Lower Bounds for Statistical Estimation Problems via a Distributed Data Processing Inequality M. Braverman A. Garg Tengyu Ma Huy Le Nguyen David P. Woodruff FedML 50 175 0 24 Jun 2015
The Expected Norm of a Sum of Independent Random Matrices: An Elementary Approach J. Tropp 54 55 0 15 Jun 2015
Deep learning with Elastic Averaging SGD Sixin Zhang A. Choromańska Yann LeCun FedML 96 610 0 20 Dec 2014
On Communication Cost of Distributed Statistical Estimation and Dimensionality A. Garg Tengyu Ma Huy Le Nguyen 73 102 0 07 May 2014
Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation Ohad Shamir 84 108 0 14 Nov 2013