• MATLAB expm

  • Referenced in 174 articles [sw14349]
  • scaling and squaring method for the matrix exponential revisited. The scaling and squaring method ... MATLAB function expm. The method scales the matrix by a power of 2 to reduce ... then repeatedly squares to undo the effect of the scaling...
  • Expint

  • Referenced in 59 articles [sw07150]
  • through a modification of the scaling and squaring technique, the most common approach used...
  • SPGL1

  • Referenced in 196 articles [sw08365]
  • SPGL1: A solver for large-scale sparse reconstruction: Probing the Pareto frontier for basis pursuit ... norm solution of an underdetermined least-squares problem. Basis Pursuit DeNoise (BPDN) fits the least ... optimal trade-off between the least-squares fit and the one-norm of the solution ... suitable for problems that are large scale and for those that are in the complex...
  • SIFT

  • Referenced in 635 articles [sw16554]
  • scene. The features are invariant to image scale and rotation, and are shown to provide ... object, and finally performing verification through least-squares solution for consistent pose parameters. This approach...
  • Harwell-Boeing sparse matrix collection

  • Referenced in 216 articles [sw08516]
  • comprises problems in linear systems, least squares, and eigenvalue calculations from a wide variety ... large test cases arising in large-scale computation. We offer the collection to other researchers...
  • Adaptative L1 TE and Predictive

  • Referenced in 19 articles [sw32154]
  • required to find the solution scales as the square of the number of timesteps. Besides ... these problems usually involve markedly different time scales, which leads to quite inhomogeneous numerical errors...
  • NNLS

  • Referenced in 15 articles [sw04749]
  • squares --- NEW software for large-scale nonnegative least squares...
  • Blendenpik

  • Referenced in 43 articles [sw09210]
  • stable. More specifically, we describe a least-squares solver for dense highly overdetermined systems that ... LAPACK), outperforms LAPACK by large factors, and scales significantly better than any QR-based solver...
  • l1_ls

  • Referenced in 10 articles [sw14267]
  • paper: A Method for Large-Scale l1-Regularized Least Squares. l1_ls is developed...
  • softImpute

  • Referenced in 83 articles [sw12263]
  • values. The second approach uses alternating least squares. Both have an ”EM” flavor, in that ... package includes procedures for centering and scaling rows, columns or both, and for computing...
  • LSRN

  • Referenced in 27 articles [sw09555]
  • dense problems, and it outperforms the least squares solver from SuiteSparseQR on sparse problems without ... fill-in. Further experiments show that LSRN scales well on an Amazon Elastic Compute Cloud...
  • Algorithm 894

  • Referenced in 3 articles [sw13925]
  • algorithms are implemented, one is the scaling and squaring method, and the other...
  • RichardsFOAM

  • Referenced in 5 articles [sw19951]
  • fluxes at the scale of experimental watersheds (up to few square kilometres of surface area...
  • LIBRA

  • Referenced in 29 articles [sw10553]
  • library contains functions for univariate location, scale and skewness, multivariate location and covariance estimation ... ROBPCA), Principal Component Regression (RPCR), Partial Least Squares Regression (RSIMPLS), classification (RDA, RSIMCA), clustering, outlier...
  • Algorithm 800

  • Referenced in 11 articles [sw04405]
  • algorithm. Routines are provided for computing the square-reduced form, computing the eigenvalues using ... easy to use), and symplectic and norm scaling. There is a comprehensive discussion ... perturbed by up to the square root of the unit rounding error. Such a loss ... sometimes (but not always) be avoided by scaling. Of the three scaling strategies mentioned (norm...
  • Jellyfish

  • Referenced in 29 articles [sw12431]
  • Parallel stochastic gradient algorithms for large-scale matrix completion. This paper develops Jellyfish, an algorithm ... Jellyfish include matrix completion problems and least-squares problems regularized by the nuclear norm ... number of processors. On large-scale matrix completion tasks, Jellyfish is orders of magnitude more...
  • N-way Toolbox

  • Referenced in 30 articles [sw12996]
  • maximization); Fitting models with a weighted least squares loss function (including MILES); Predicting scores ... models; Performing multi-way scaling and centering; Performing cross-validation of models; Calculating core consistency...
  • FALSCAL

  • Referenced in 1 article [sw02608]
  • algorithm The conventionally adopted Alternating Least squares SCALing (ALSCAL) procedure of multidimensional scaling...
  • 2HDECAY

  • Referenced in 2 articles [sw40158]
  • Exceptions are the soft-ℤ2-breaking squared mass scale m212, where an MS condition...
  • SPARSE-QR

  • Referenced in 17 articles [sw05215]
  • sparse QR factorization. Sparse linear least squares problems are instead solved by the augmented system ... computed solutions is strongly dependent on a scaling parameter δ. Its optimal value is expensive ... solution of sparse linear least squares problems and compare these with the built-in MATLAB...