• LAPACK

  • Referenced in 1713 articles [sw00503]
  • equations, eigenvalue problems, and singular value problems. The associated matrix factorizations (LU, Cholesky...
  • UTV

  • Referenced in 272 articles [sw05213]
  • type problems with a rank-deficient covariance matrix, and we provide a robust and reliable ... dominant singular values of a sparse or structured matrix. These new algorithms have applications...
  • OptShrink

  • Referenced in 20 articles [sw33657]
  • rank signal matrix denoising by optimal, data-driven singular value shrinkage. OptShrink is a simple ... matrix buried in noise. It takes as its input the signal-plus-noise matrix ... improved signal matrix estimate. It computes this estimate by shrinking the singular values corresponding ... will always do better than singular value thresholding...
  • Multilinear Engine

  • Referenced in 34 articles [sw14430]
  • determined by inspecting the singular values of the Jacobian matrix. A global solution...
  • NAPACK

  • Referenced in 71 articles [sw11666]
  • matrix by a vector, to invert a matrix, to solve least squares problems, to perform ... minimization, to compute eigenvalues, eigenvectors, the singular value decomposition, or the QR decomposition. The package...
  • corpor

  • Referenced in 24 articles [sw09381]
  • shrinkage correlation matrix. Furthermore, functions are available for fast singular value decomposition, for computing ... rank and positive definiteness of a matrix...
  • DLASQ

  • Referenced in 6 articles [sw08636]
  • Superquadratic convergence of DLASQ for computing matrix singular values. DLASQ is a routine in LAPACK ... computing the singular values of a real upper bidiagonal matrix with high accuracy. The basic ... most efficient routines for computing singular values. In this paper, we prove the asymptotic superquadratic...
  • hapod

  • Referenced in 14 articles [sw40605]
  • left singular vectors, and singular values of a matrix) hierarchically for (column-wise partitioned) large...
  • Tensorlab

  • Referenced in 77 articles [sw14255]
  • structured data fusion: define your own (coupled) matrix and tensor factorizations with structured factors ... decompositions: canonical polyadic decomposition (CPD), multilinear singular value decomposition (MLSVD), block term decompositions...
  • na26

  • Referenced in 25 articles [sw11493]
  • smallest singular values and associated singular vectors of a large matrix arises in many applications...
  • corpcor

  • Referenced in 15 articles [sw10199]
  • shrinkage correlation matrix. Furthermore, functions are available for fast singular value decomposition, for computing ... rank and positive definiteness of a matrix...
  • denoiseR

  • Referenced in 8 articles [sw17854]
  • data using singular values thresholding and shrinking functions. Impute missing values with matrix completion...
  • Optspace

  • Referenced in 8 articles [sw12630]
  • problem of reconstructing a low-rank matrix from a small subset of its entries ... singular value decomposition followed by local manifold optimization, for solving the low-rank matrix completion ... output of singular value decomposition gives a good estimate for the original matrix, so that...
  • irbleigs

  • Referenced in 19 articles [sw00451]
  • accessed only through the evaluation of matrix-vector products. Working space of only ... singular values and associated right and left singular vectors of a large general matrix...
  • Algorithm 844

  • Referenced in 18 articles [sw04407]
  • sparse matrix A. Unfortunately, the approximations based on traditional decompositions, like the singular value...
  • impute

  • Referenced in 104 articles [sw14376]
  • expression analysis require a complete matrix of gene array values as input. For example, methods ... lose effectiveness even with a few missing values. Methods for imputing missing data are needed ... missing values in gene microarray data. We implemented and evaluated three methods: a Singular Value...
  • OEIG

  • Referenced in 4 articles [sw07166]
  • efficient algorithm for solving it. Usually, the matrix pencil {𝐀-λ𝐁} does not have ... that locally minimize the smallest singular value over the matrix pencil {𝐀-λ𝐁}. Practically...
  • RSpectra

  • Referenced in 7 articles [sw15409]
  • eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, which is usually ... largest k singular values and corresponding singular vectors of a real matrix. Matrices...
  • ARAP++

  • Referenced in 4 articles [sw36689]
  • convex combination weights and a fitting Jacobian matrix corresponding to a prescribed family of transformations ... appropriately prescribing the singular values of the fitting matrix. To reduce the area and stretch...
  • svt

  • Referenced in 1 article [sw37232]
  • Singular Value Thresholding in MATLAB. Many statistical learning methods such as matrix completion, matrix regression ... most time-consuming step is singular value ... thresholding, which seeks the singular values of a large matrix exceeding a threshold and their ... sparse matrix input, while aforementioned statistical learning algorithms perform singular value thresholding on dense...