CPQR-based randomized algorithms for generalized CUR decompositions

03/13/2023
by   Guihua Zhang, et al.
0

Based on the column pivoted QR decomposition, we propose some randomized algorithms including pass-efficient ones for the generalized CUR decompositions of matrix pair and matrix triplet. Detailed error analyses of these algorithms are provided. Numerical experiments are given to test the proposed randomized algorithms.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/23/2017

Triangular Decomposition of Matrices in a Domain

Deterministic recursive algorithms for the computation of matrix triangu...
research
08/06/2016

Randomized Matrix Decompositions using R

Matrix decompositions are fundamental tools in the area of applied mathe...
research
04/13/2021

Simpler is better: A comparative study of randomized algorithms for computing the CUR decomposition

The CUR decomposition is a technique for low-rank approximation that sel...
research
04/14/2021

Stable and Efficient Computation of Generalized Polar Decompositions

We present methods for computing the generalized polar decomposition of ...
research
10/05/2021

Efficient GPU implementation of randomized SVD and its applications

Matrix decompositions are ubiquitous in machine learning, including appl...
research
11/22/2021

A Novel Randomized XR-Based Preconditioned CholeskyQR Algorithm

CholeskyQR is a simple and fast QR decomposition via Cholesky decomposit...
research
11/29/2021

A theory of meta-factorization

This paper introduces meta-factorization, a theory that describes matrix...

Please sign up or login with your details

Forgot password? Click here to reset