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A block-sparse Tensor Train Format for sample-efficient high-dimensional Polynomial Regression

A block-sparse Tensor Train Format for sample-efficient high-dimensional Polynomial Regression

M. Götte
R. Schneider
Philipp Trunschke
ArXiv (abs)PDFHTML

Papers citing "A block-sparse Tensor Train Format for sample-efficient high-dimensional Polynomial Regression"

4 / 4 papers shown
Title
Solving high-dimensional parabolic PDEs using the tensor train format
Solving high-dimensional parabolic PDEs using the tensor train format
Lorenz Richter
Leon Sallandt
Nikolas Nusken
84
50
0
23 Feb 2021
Tensor-based algorithms for image classification
Tensor-based algorithms for image classification
Stefan Klus
Patrick Gelß
71
31
0
04 Oct 2019
Optimal weighted least-squares methods
Optimal weighted least-squares methods
A. Cohen
G. Migliorati
69
197
0
01 Aug 2016
A least-squares method for sparse low rank approximation of multivariate functions
A least-squares method for sparse low rank approximation of multivariate functions
M. Chevreuil
R. Lebrun
A. Nouy
Prashant Rai
63
103
0
30 Apr 2013

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