• LINPACK

  • Referenced in 518 articles [sw04209]
  • package computes the QR and singular value decompositions of rectangular matrices and applies them...
  • EISPACK

  • Referenced in 486 articles [sw04208]
  • routines are included that use singular value decomposition to solve certain least-squares problems. EISPACK...
  • SLEPc

  • Referenced in 180 articles [sw00875]
  • other related problems such as the singular value decomposition or the quadratic eigenvalue problem...
  • PROPACK

  • Referenced in 109 articles [sw04019]
  • functions for computing the singular value decomposition of large and sparse or structured matrices...
  • impute

  • Referenced in 99 articles [sw14376]
  • implemented and evaluated three methods: a Singular Value Decomposition (SVD) based method (SVDimpute), weighted...
  • Tensorlab

  • Referenced in 63 articles [sw14255]
  • decompositions: canonical polyadic decomposition (CPD), multilinear singular value decomposition (MLSVD), block term decompositions...
  • NAPACK

  • Referenced in 71 articles [sw11666]
  • minimization, to compute eigenvalues, eigenvectors, the singular value decomposition, or the QR decomposition. The package...
  • svdpack

  • Referenced in 60 articles [sw04819]
  • numerical (iterative) methods for computing the singular value decomposition (SVD) of large sparse matrices using ... determining several of the largest singular triplets (singular values and corresponding left- and right-singular...
  • Chebfun2

  • Referenced in 38 articles [sw12708]
  • some relevant issues as global optimization, singular value decomposition, root finding, and vector calculus...
  • LSRN

  • Referenced in 24 articles [sw09555]
  • which is embarrassingly parallel, and a singular value decomposition of size ⌈γmin ... strong concentration result on the extreme singular values, and hence that the number of iterations...
  • corpor

  • Referenced in 22 articles [sw09381]
  • Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse...
  • UTV

  • Referenced in 256 articles [sw05213]
  • expand the algorithms for the ULLV decomposition of a matrix pair to handle interference-type ... able to capture all the dominant singular values of a sparse or structured matrix. These...
  • CULA

  • Referenced in 11 articles [sw12745]
  • results from factorizations such as LU decomposition, singular value decomposition and QR decomposition along with...
  • corpcor

  • Referenced in 14 articles [sw10199]
  • Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse...
  • Algorithm 844

  • Referenced in 18 articles [sw04407]
  • approximations based on traditional decompositions, like the singular value and QR decompositions...
  • rsvd

  • Referenced in 7 articles [sw16104]
  • package rsvd. Randomized singular value decomposition (rsvd) is a very fast probabilistic algorithm that ... compute the near optimal low-rank singular value decomposition of massive data sets with high ... Randomized PCA (rpca) uses the approximated singular value decomposition to compute the most significant principal...
  • TKPSVD

  • Referenced in 11 articles [sw28028]
  • propose the tensor Kronecker product singular value decomposition (TKPSVD) that decomposes a real...
  • FaIMS

  • Referenced in 8 articles [sw06425]
  • algorithm to compute an approximate singular value decomposition (SVD) of least-squares operators related ... medium perturbation, a dense singular value decomposition of the Born operator requires...
  • irlba

  • Referenced in 7 articles [sw21041]
  • package irlba: Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense ... memory efficient methods for truncated singular value decomposition and principal components analysis of large sparse...
  • SOFAR

  • Referenced in 7 articles [sw31665]
  • factor regression (SOFAR) via the sparse singular value decomposition with orthogonality constrained optimization to learn ... tasks, such as biclustering with sparse singular value decomposition, sparse principal component analysis, sparse factor...