
Chebfun2
 Referenced in 41 articles
[sw12708]
 form u(y)v(x) (low rank approximants), where ... Chebfun objects. The socalled low rank approximations are constructed using an iterative algorithm that ... variables is of low rank or can be approximated by one of this type...

ALEA
 Referenced in 60 articles
[sw10167]
 python framework for spectral methods and lowrank approximations in uncertainty quantification. ALEA is intended...

Tensorlab
 Referenced in 77 articles
[sw14255]
 block term decompositions (BTD) and low multilinear rank approximation (LMLRA), complex optimization: quasiNewton...

ADMiRA
 Referenced in 35 articles
[sw31664]
 lowrank matrix posing the inverse problem as an approximation problem with a specified target ... sparse vector and a lowrank matrix and extending efficient greedy algorithms from the vector ... lowrank matrix case. The performance guarantee is given in terms of the rankrestricted ... general case of noisy measurements and approximately lowrank solution. With a sparse measurement operator...

NLEIGS
 Referenced in 34 articles
[sw22547]
 target set, and it also features lowrank approximation techniques for increased computational efficiency. Small...

JIVE
 Referenced in 22 articles
[sw09511]
 decomposition consists of three terms: a lowrank approximation capturing joint variation across data types ... lowrank approximations for structured variation individual to each data type, and residual noise. JIVE...

UQLab
 Referenced in 43 articles
[sw19740]
 Gaussian process modelling, a.k.a. Kriging, lowrank tensor approximations), rare event estimation (structural reliability), global...

SLRA
 Referenced in 24 articles
[sw11262]
 presents optimization methods and software for the approximate GCD problem of multiple univariate polynomials ... norm. Backward error minimization and Sylvester lowrank approximation formulations of the problem are solved...

RandNLA
 Referenced in 23 articles
[sw41749]
 matrix multiplication, leastsquares (LS) approximation, lowrank matrix approximation, and Laplacianbased linear equation...

Algorithm 844
 Referenced in 18 articles
[sw04407]
 reduced rank approximation to a sparse matrix A. Unfortunately, the approximations based on traditional decompositions ... algorithm, to obtain two kinds of lowrank approximations. The first, the SPQR, approximation...

SymNMF
 Referenced in 15 articles
[sw12668]
 SymNMF: nonnegative lowrank approximation of a similarity matrix for graph clustering. Nonnegative matrix factorization...

Algorithm 971
 Referenced in 10 articles
[sw22686]
 intense development of randomized methods for lowrank approximation. These methods target principal component analysis ... several tests, the randomized algorithms for lowrank approximation outperform or at least match...

FFTSVD
 Referenced in 10 articles
[sw08886]
 octree and uses sampling to calculate lowrank approximations to dominant source distributions and responses...

SingularIntegralEquations
 Referenced in 10 articles
[sw22771]
 systems. This is accomplished by utilizing low rank approximations for sparse representations of the bivariate...

Colibri
 Referenced in 9 articles
[sw12043]
 large static and dynamic graphs. Lowrank approximations of the adjacency matrix of a graph ... desirable to track the lowrank structure as the graph evolves over time, efficiently...

hubauth
 Referenced in 9 articles
[sw38374]
 three different algorithms: Gauss quadrature, lowrank approximation, and a hybrid method. The functions were...

ID
 Referenced in 4 articles
[sw14543]
 software package for lowrank approximation of matrices via interpolative decompositions. This software distribution provides ... Fortran routines for computing lowrank approximations to matrices, in the forms of interpolative decompositions ... approximation obtained via skeletonization, the approximation obtained via subsampling, and the approximation obtained via subset ... well as tools for computing lowrank approximations in the form of SVDs. Section...

LOBPCG
 Referenced in 33 articles
[sw09638]
 Preconditioned lowrank methods for highdimensional elliptic PDE eigenvalue problems. We consider elliptic ... addressed by approximating the desired solution vector x in a lowrank tensor format...

PNKHB
 Referenced in 4 articles
[sw40451]
 gradient evaluations are expensive, and the (approximate) Hessian is only available through matrixvector products ... each iteration, PNKHB uses a lowrank approximation of the (approximate) Hessian to determine ... metric is its consistency with the lowrank approximation of the Hessian on the Krylov ... interior point method effectively exploits the lowrank structure, its computational cost only scales linearly...

NeNMF
 Referenced in 34 articles
[sw17586]
 technique that approximates a nonnegative matrix by the product of two lowrank nonnegative matrix ... terms of efficiency as well as approximation accuracy. Compared to PNLS and AS that suffer...