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Diversity sampling is an implicit regularization for kernel methods

Diversity sampling is an implicit regularization for kernel methods

SIAM Journal on Mathematics of Data Science (SIMODS), 2020
20 February 2020
Michaël Fanuel
J. Schreurs
Johan A. K. Suykens
ArXiv (abs)PDFHTML

Papers citing "Diversity sampling is an implicit regularization for kernel methods"

9 / 9 papers shown
On sampling determinantal and Pfaffian point processes on a quantum
  computer
On sampling determinantal and Pfaffian point processes on a quantum computer
Rémi Bardenet
Michaël Fanuel
A. Feller
360
2
0
25 May 2023
Deep Kernel Principal Component Analysis for Multi-level Feature
  Learning
Deep Kernel Principal Component Analysis for Multi-level Feature LearningNeural Networks (Neural Netw.), 2023
F. Tonin
Qinghua Tao
Panagiotis Patrinos
Johan A. K. Suykens
246
42
0
22 Feb 2023
Randomly pivoted Cholesky: Practical approximation of a kernel matrix
  with few entry evaluations
Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations
Yifan Chen
Ethan N. Epperly
J. Tropp
R. Webber
642
58
0
13 Jul 2022
Determinantal Point Processes Implicitly Regularize Semi-parametric
  Regression Problems
Determinantal Point Processes Implicitly Regularize Semi-parametric Regression ProblemsSIAM Journal on Mathematics of Data Science (SIMODS), 2020
Michaël Fanuel
J. Schreurs
Johan A. K. Suykens
203
4
0
13 Nov 2020
Sample and Computationally Efficient Stochastic Kriging in High
  Dimensions
Sample and Computationally Efficient Stochastic Kriging in High Dimensions
Liang Ding
Xiaowei Zhang
311
10
0
14 Oct 2020
Ensemble Kernel Methods, Implicit Regularization and Determinantal Point
  Processes
Ensemble Kernel Methods, Implicit Regularization and Determinantal Point Processes
J. Schreurs
Michaël Fanuel
Johan A. K. Suykens
425
2
0
24 Jun 2020
Precise expressions for random projections: Low-rank approximation and
  randomized Newton
Precise expressions for random projections: Low-rank approximation and randomized Newton
Michal Derezinski
Feynman T. Liang
Zhenyu A. Liao
Michael W. Mahoney
486
25
0
18 Jun 2020
Determinantal Point Processes in Randomized Numerical Linear Algebra
Determinantal Point Processes in Randomized Numerical Linear Algebra
Michal Derezinski
Michael W. Mahoney
281
93
0
07 May 2020
Nyström landmark sampling and regularized Christoffel functions
Nyström landmark sampling and regularized Christoffel functionsMachine-mediated learning (ML), 2019
Michaël Fanuel
J. Schreurs
Johan A. K. Suykens
376
15
0
29 May 2019
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