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An implementation of a randomized algorithm for principal component
  analysis

An implementation of a randomized algorithm for principal component analysis

11 December 2014
Arthur Szlam
Y. Kluger
M. Tygert
ArXiv (abs)PDFHTML

Papers citing "An implementation of a randomized algorithm for principal component analysis"

7 / 7 papers shown
Title
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced
  order models for nonlinear parametrized PDEs
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs
Simone Brivio
S. Fresca
Andrea Manzoni
AI4CE
76
7
0
14 May 2024
POD-DL-ROM: enhancing deep learning-based reduced order models for
  nonlinear parametrized PDEs by proper orthogonal decomposition
POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition
S. Fresca
Andrea Manzoni
AI4CE
69
219
0
28 Jan 2021
Randomized Nonnegative Matrix Factorization
Randomized Nonnegative Matrix Factorization
N. Benjamin Erichson
Ariana Mendible
Sophie Wihlborn
J. Nathan Kutz
67
52
0
06 Nov 2017
Randomized CP Tensor Decomposition
Randomized CP Tensor Decomposition
N. Benjamin Erichson
Krithika Manohar
Steven L. Brunton
J. Nathan Kutz
89
64
0
27 Mar 2017
Randomized Matrix Decompositions using R
Randomized Matrix Decompositions using R
N. Benjamin Erichson
S. Voronin
Steven L. Brunton
J. Nathan Kutz
89
145
0
06 Aug 2016
Randomized Block Krylov Methods for Stronger and Faster Approximate
  Singular Value Decomposition
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition
Cameron Musco
Christopher Musco
94
20
0
21 Apr 2015
Dimensionality Reduction for k-Means Clustering and Low Rank
  Approximation
Dimensionality Reduction for k-Means Clustering and Low Rank Approximation
Michael B. Cohen
Sam Elder
Cameron Musco
Christopher Musco
Madalina Persu
150
361
0
24 Oct 2014
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