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Randomized sketches for kernels: Fast and optimal non-parametric
  regression

Randomized sketches for kernels: Fast and optimal non-parametric regression

25 January 2015
Yun Yang
Mert Pilanci
Martin J. Wainwright
ArXiv (abs)PDFHTML

Papers citing "Randomized sketches for kernels: Fast and optimal non-parametric regression"

14 / 64 papers shown
Title
Improved Fixed-Rank Nyström Approximation via QR Decomposition:
  Practical and Theoretical Aspects
Improved Fixed-Rank Nyström Approximation via QR Decomposition: Practical and Theoretical Aspects
Farhad Pourkamali Anaraki
Stephen Becker
47
24
0
08 Aug 2017
Sketched Subspace Clustering
Sketched Subspace Clustering
Panagiotis A. Traganitis
G. Giannakis
77
51
0
22 Jul 2017
Early stopping for kernel boosting algorithms: A general analysis with
  localized complexities
Early stopping for kernel boosting algorithms: A general analysis with localized complexities
Yuting Wei
Fanny Yang
Martin J. Wainwright
90
77
0
05 Jul 2017
Approximate Kernel PCA Using Random Features: Computational vs.
  Statistical Trade-off
Approximate Kernel PCA Using Random Features: Computational vs. Statistical Trade-off
Bharath K. Sriperumbudur
Nicholas Sterge
101
22
0
20 Jun 2017
Understanding the Learned Iterative Soft Thresholding Algorithm with
  matrix factorization
Understanding the Learned Iterative Soft Thresholding Algorithm with matrix factorization
Thomas Moreau
Joan Bruna
64
15
0
02 Jun 2017
FALKON: An Optimal Large Scale Kernel Method
FALKON: An Optimal Large Scale Kernel Method
Alessandro Rudi
Luigi Carratino
Lorenzo Rosasco
108
196
0
31 May 2017
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel
  Methods and Neural Networks
On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks
A. Backurs
Piotr Indyk
Ludwig Schmidt
125
40
0
10 Apr 2017
Sharper Bounds for Regularized Data Fitting
Sharper Bounds for Regularized Data Fitting
H. Avron
K. Clarkson
David P. Woodruff
85
58
0
10 Nov 2016
Faster Kernel Ridge Regression Using Sketching and Preconditioning
Faster Kernel Ridge Regression Using Sketching and Preconditioning
H. Avron
K. Clarkson
David P. Woodruff
127
125
0
10 Nov 2016
Understanding Trainable Sparse Coding via Matrix Factorization
Understanding Trainable Sparse Coding via Matrix Factorization
Thomas Moreau
Joan Bruna
74
45
0
01 Sep 2016
Kernel Ridge Regression via Partitioning
Kernel Ridge Regression via Partitioning
Rashish Tandon
Si Si
Pradeep Ravikumar
Inderjit Dhillon
16
18
0
05 Aug 2016
Optimal approximate matrix product in terms of stable rank
Optimal approximate matrix product in terms of stable rank
Michael B. Cohen
Jelani Nelson
David P. Woodruff
93
132
0
08 Jul 2015
Iterative Hessian sketch: Fast and accurate solution approximation for
  constrained least-squares
Iterative Hessian sketch: Fast and accurate solution approximation for constrained least-squares
Mert Pilanci
Martin J. Wainwright
123
206
0
03 Nov 2014
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with
  Minimax Optimal Rates
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
Yuchen Zhang
John C. Duchi
Martin J. Wainwright
375
379
0
22 May 2013
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