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Kernel Conjugate Gradient Methods with Random Projections

Kernel Conjugate Gradient Methods with Random Projections

5 November 2018
Bailey Kacsmar
Douglas R Stinson
ArXivPDFHTML

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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
An Introduction to Matrix Concentration Inequalities
J. Tropp
153
1,149
0
07 Jan 2015
Fast Randomized Kernel Methods With Statistical Guarantees
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
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
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
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
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
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
Optimal learning rates for Kernel Conjugate Gradient regression
Gilles Blanchard
Nicole Krämer
84
71
0
29 Sep 2010
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