v1v2 (latest)

Kernel Conjugate Gradient Methods with Random Projections

5 November 2018

Papers citing "Kernel Conjugate Gradient Methods with Random Projections"

22 / 22 papers shown

Title
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing Jian Guo He He Tong He Leonard Lausen Mu Li ... Hang Zhang Zhi-Li Zhang Zhongyue Zhang Shuai Zheng Yi Zhu VLM BDL 77 198 0 09 Jul 2019
Analysis of regularized Nyström subsampling for regression functions of low smoothness Shuai Lu Peter Mathé S. Pereverzyev 67 18 0 03 Jun 2018
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces Junhong Lin Volkan Cevher 30 9 0 12 Mar 2018
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms Junhong Lin Volkan Cevher 57 34 0 22 Jan 2018
Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces Junhong Lin Alessandro Rudi Lorenzo Rosasco Volkan Cevher 147 99 0 20 Jan 2018
Lectures on Randomized Numerical Linear Algebra P. Drineas Michael W. Mahoney 52 77 0 24 Dec 2017
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice Hongzhou Lin Julien Mairal Zaïd Harchaoui 62 139 0 15 Dec 2017
Kernel partial least squares for stationary data Marco Singer Tatyana Krivobokova Axel Munk 35 7 0 12 Jun 2017
FALKON: An Optimal Large Scale Kernel Method Alessandro Rudi Luigi Carratino Lorenzo Rosasco 83 196 0 31 May 2017
Faster Kernel Ridge Regression Using Sketching and Preconditioning H. Avron K. Clarkson David P. Woodruff 108 125 0 10 Nov 2016
Convergence rates of Kernel Conjugate Gradient for random design regression Gilles Blanchard Nicole E. Kramer 55 38 0 08 Jul 2016
Optimal Rates For Regularization Of Statistical Inverse Learning Problems Gilles Blanchard Nicole Mücke 473 143 0 14 Apr 2016
Less is More: Nyström Computational Regularization Alessandro Rudi Raffaello Camoriano Lorenzo Rosasco 63 277 0 16 Jul 2015
Randomized sketches for kernels: Fast and optimal non-parametric regression Yun Yang Mert Pilanci Martin J. Wainwright 95 174 0 25 Jan 2015
An Introduction to Matrix Concentration Inequalities J. Tropp 178 1,155 0 07 Jan 2015
Fast Randomized Kernel Methods With Statistical Guarantees A. Alaoui Michael W. Mahoney 121 90 0 02 Nov 2014
Early stopping and non-parametric regression: An optimal data-dependent stopping rule Garvesh Raskutti Martin J. Wainwright Bin Yu 136 299 0 15 Jun 2013
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning Alex Gittens Michael W. Mahoney 120 416 0 07 Mar 2013
Sharp analysis of low-rank kernel matrix approximations Francis R. Bach 175 282 0 09 Aug 2012
On Some Extensions of Bernstein's Inequality for Self-adjoint Operators Stanislav Minsker 244 152 0 22 Dec 2011
Fast approximation of matrix coherence and statistical leverage P. Drineas M. Magdon-Ismail Michael W. Mahoney David P. Woodruff 168 533 0 18 Sep 2011
Optimal learning rates for Kernel Conjugate Gradient regression Gilles Blanchard Nicole Krämer 107 71 0 29 Sep 2010