• ScaLAPACK

  • Referenced in 407 articles [sw00830]
  • matrix inversion, full-rank linear least squares problems, orthogonal and generalized orthogonal factorizations, orthogonal transformation...
  • LAPACK

  • Referenced in 1647 articles [sw00503]
  • least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems ... matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related...
  • LINPACK

  • Referenced in 514 articles [sw04209]
  • linear least-squares problems. The package solves linear systems whose matrices are general, banded, symmetric ... indefinite, symmetric positive definite, triangular, and tridiagonal square. In addition, the package computes ... rectangular matrices and applies them to least-squares problems. LINPACK uses column-oriented algorithms...
  • NAPACK

  • Referenced in 71 articles [sw11666]
  • optimization. It may be used to solve linear systems, to estimate the condition number ... invert a matrix, to solve least squares problems, to perform unconstrained minimization, to compute eigenvalues ... decomposition. The package has special routines for general, band, symmetric, indefinite, tridiagonal, upper Hessenberg...
  • Ceres Solver

  • Referenced in 8 articles [sw20619]
  • solve Non-linear Least Squares problems with bounds constraints and general unconstrained optimization problems...
  • nlr

  • Referenced in 9 articles [sw05244]
  • quasi-likelihood, generalized nonlinear least squares, and some robust fitting problems. The accompanying test examples ... include members of the generalized linear model family, extensions using nonlinear predictors (“nonlinear GLIM ... such as linear-in-parameter multinomial probit models. The basic method, a generalization ... NL2SOL algorithm for nonlinear least squares, employs a model/trust-region scheme for computing trial steps, exploits...
  • MINRES-QLP

  • Referenced in 20 articles [sw11181]
  • solving symmetric or Hermitian linear systems or least-squares problems. If the system is singular ... also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes...
  • MINRES

  • Referenced in 33 articles [sw13371]
  • conjugate-gradient type method for solving sparse linear equations: Solve ... really solving one of the least-squares problems minimize ... least-squares solution with small ||Ar|| (where r=b−Ax), but in general...
  • TENSOLVE

  • Referenced in 28 articles [sw00956]
  • systems of nonlinear equations and nonlinear least-squares problems using tensor methods. This article describes ... solving systems of nonlinear equations and nonlinear problems, using a new class of methods called ... intended for small- to medium-sized problems, say with up to 100 equations and unknowns ... standard method based on a linear model. The tensor method approximates...
  • LS-SVMlab

  • Referenced in 26 articles [sw07367]
  • recent developments in kernel based methods in general. Originally, it has been introduced within ... solves convex optimization problems, typically quadratic programs. Least Squares Support Vector Machines ... standard SVMs which lead to solving linear KKT systems. LS-SVMs are closely related...
  • QPOPT

  • Referenced in 17 articles [sw07859]
  • QPOPT: Fortran package for constrained linear least-squares and convex quadratic programming. QPOPT ... subroutines for minimizing a general quadratic function subject to linear constraints and simple upper ... linear programming and for finding a feasible point for a set of linear equalities ... QPOPT is not intended for large sparse problems, but there is no fixed limit...
  • ParaSails

  • Referenced in 27 articles [sw11521]
  • with 216 million equations. ParaSails uses least-squares (Frobenius norm) minimization to compute a sparse ... sequence of linear solves. ParaSails solves symmetric positive definite (SPD) problems using a factorized ... preconditioner. ParaSails can also solve general (nonsymmetric and/or indefinite) problems with a nonfactorized preconditioner...
  • BCSLIB-EXT

  • Referenced in 3 articles [sw13150]
  • linear equations, large sparse least squares problems, solution of large sparse real symmetric generalized eigenproblems ... core solution of large dense systems of linear equations, out-of-core solution of real...
  • GELDA

  • Referenced in 33 articles [sw00331]
  • example, in the solution of linear quadratic optimal control problems and differential-algebraic Riccati equations ... many of the standard integration methods for general DAEs require the system to have differentiation ... properties can be treated in a least squares sense. In the case that...
  • sparseLM

  • Referenced in 5 articles [sw04810]
  • cumulative geometric error using non-linear least-squares fitting. Typically, this error is characterized ... estimated, which leads to minimization problems possessing a sparse structure. Taking advantage of this sparseness ... sparsity pattern is problem-dependent, its exploitation for a particular estimation problem requires non-trivial ... sparseLM, a general-purpose software package for sparse non-linear least squares that can exhibit...
  • SDLS

  • Referenced in 8 articles [sw04788]
  • solve approximately convex conic least-squares problems. Geometrically, these problems amount to finding the projection ... affine subspace. SDLS solves the dual problem with a quasi-Newton minimization algorithm, using ... matrices, achieved by Matlab’s built-in linear algebra functions. Note that SDLS ... solving and experimenting with general conic least-squares. Up to our knowledge, no such freeware...
  • dqed

  • Referenced in 3 articles [sw05224]
  • presented for solving nonlinear least squares and nonlinear equation problems. The algorithm is based ... problem statement may include simple bounds or more general linear constraints on the unknowns ... computations for the model-problem require a constrained nonlinear least squares solver. This is done...
  • TOMSYM

  • Referenced in 3 articles [sw06288]
  • Optimizer. The environment is included with the general TOMLAB Base Module. The class allows ... problem types, including: Linear and quadratic programming Nonlinear and semidefinite programming Least squares problem...
  • g2o

  • Referenced in 8 articles [sw22795]
  • general framework for graph optimization. g2o is an open-source C++ framework for optimizing graph ... wide range of problems and a new problem typically can be specified ... SLAM and BA. A wide range of problems in robotics as well as in computer ... source C++ framework for such nonlinear least squares problems. g2o has been designed...
  • NCL

  • Referenced in 1 article [sw36527]
  • general smooth optimization problems where first and second derivatives are available, including problems whose constraints ... linearly independent at a solution (i.e., do not satisfy the LICQ). It is equivalent ... LICQ, and on nonlinear least-squares problems and general problems from the CUTEst test...