Decentralised Learning with Random Features and Distributed Gradient Descent

1 July 2020

Papers citing "Decentralised Learning with Random Features and Distributed Gradient Descent"

9 / 9 papers shown

Title
On Fast Leverage Score Sampling and Optimal Learning Alessandro Rudi Daniele Calandriello Luigi Carratino Lorenzo Rosasco 63 82 0 31 Oct 2018
Learning with SGD and Random Features Luigi Carratino Alessandro Rudi Lorenzo Rosasco 53 78 0 17 Jul 2018
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees H. Avron Michael Kapralov Cameron Musco Christopher Musco A. Velingker A. Zandieh 73 156 0 26 Apr 2018
Optimal algorithms for smooth and strongly convex distributed optimization in networks Kevin Scaman Francis R. Bach Sébastien Bubeck Y. Lee Laurent Massoulié 86 331 0 28 Feb 2017
Orthogonal Random Features Felix X. Yu A. Suresh K. Choromanski D. Holtmann-Rice Sanjiv Kumar 96 222 0 28 Oct 2016
Distributed learning with regularized least squares Shaobo Lin Xin Guo Ding-Xuan Zhou 162 191 0 11 Aug 2016
Optimal Rates For Regularization Of Statistical Inverse Learning Problems Gilles Blanchard Nicole Mücke 471 143 0 14 Apr 2016
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates Yuchen Zhang John C. Duchi Martin J. Wainwright 331 379 0 22 May 2013
Sharp analysis of low-rank kernel matrix approximations Francis R. Bach 175 282 0 09 Aug 2012