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1811.01760
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Kernel Conjugate Gradient Methods with Random Projections
5 November 2018
Bailey Kacsmar
Douglas R Stinson
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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
66
197
0
09 Jul 2019
Analysis of regularized Nyström subsampling for regression functions of low smoothness
Shuai Lu
Peter Mathé
S. Pereverzyev
55
18
0
03 Jun 2018
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces
Junhong Lin
Volkan Cevher
23
9
0
12 Mar 2018
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms
Junhong Lin
Volkan Cevher
45
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
128
99
0
20 Jan 2018
Lectures on Randomized Numerical Linear Algebra
P. Drineas
Michael W. Mahoney
36
76
0
24 Dec 2017
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice
Hongzhou Lin
Julien Mairal
Zaïd Harchaoui
38
139
0
15 Dec 2017
Kernel partial least squares for stationary data
Marco Singer
Tatyana Krivobokova
Axel Munk
25
7
0
12 Jun 2017
FALKON: An Optimal Large Scale Kernel Method
Alessandro Rudi
Luigi Carratino
Lorenzo Rosasco
75
196
0
31 May 2017
Faster Kernel Ridge Regression Using Sketching and Preconditioning
H. Avron
K. Clarkson
David P. Woodruff
65
125
0
10 Nov 2016
Convergence rates of Kernel Conjugate Gradient for random design regression
Gilles Blanchard
Nicole E. Kramer
40
38
0
08 Jul 2016
Optimal Rates For Regularization Of Statistical Inverse Learning Problems
Gilles Blanchard
Nicole Mücke
439
143
0
14 Apr 2016
Less is More: Nyström Computational Regularization
Alessandro Rudi
Raffaello Camoriano
Lorenzo Rosasco
43
277
0
16 Jul 2015
Randomized sketches for kernels: Fast and optimal non-parametric regression
Yun Yang
Mert Pilanci
Martin J. Wainwright
77
174
0
25 Jan 2015
An Introduction to Matrix Concentration Inequalities
J. Tropp
153
1,149
0
07 Jan 2015
Fast Randomized Kernel Methods With Statistical Guarantees
A. Alaoui
Michael W. Mahoney
83
90
0
02 Nov 2014
Early stopping and non-parametric regression: An optimal data-dependent stopping rule
Garvesh Raskutti
Martin J. Wainwright
Bin Yu
108
299
0
15 Jun 2013
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning
Alex Gittens
Michael W. Mahoney
115
414
0
07 Mar 2013
Sharp analysis of low-rank kernel matrix approximations
Francis R. Bach
152
282
0
09 Aug 2012
On Some Extensions of Bernstein's Inequality for Self-adjoint Operators
Stanislav Minsker
146
151
0
22 Dec 2011
Fast approximation of matrix coherence and statistical leverage
P. Drineas
M. Magdon-Ismail
Michael W. Mahoney
David P. Woodruff
145
533
0
18 Sep 2011
Optimal learning rates for Kernel Conjugate Gradient regression
Gilles Blanchard
Nicole Krämer
84
71
0
29 Sep 2010
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