- Referenced in 513 articles
- applies them to least-squares problems. LINPACK uses column-oriented algorithms to increase efficiency...
- Referenced in 354 articles
- Algorithm 583: LSQR: Sparse Linear Equations and Least Squares Problems. An iterative method is given ... comparing LSQR with several other conjugate-gradient algorithms, indicating that LSQR is the most reliable...
- Referenced in 602 articles
- known objects using a fast nearest-neighbor algorithm, followed by a Hough transform to identify ... object, and finally performing verification through least-squares solution for consistent pose parameters. This approach...
- Referenced in 54 articles
- levmar : Levenberg-Marquardt nonlinear least squares algorithms in C/C++ This site provides GPL native ANSI ... variants are included. The Levenberg-Marquardt (LM) algorithm is an iterative technique that finds ... become a standard technique for nonlinear least-squares problems and can be thought ... from the correct one, the algorithm behaves like a steepest descent method: slow, but guaranteed...
- Referenced in 213 articles
- problem: computational aspects and analysis. Total least squares (TLS) is one of the several linear ... computationally efficient and numerically reliable TLS algorithms. Much attention is paid in this book...
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- Algorithm 573: NL2SOL—An Adaptive Nonlinear Least-Squares Algorithm...
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- time series data with a stepwise least squares algorithm that is computationally efficient, in particular...
- Referenced in 283 articles
- quadratic programming, nonlinear optimization, and nonlinear least squares. You can use these solvers to find ... tradeoff analyses, and incorporate optimization methods into algorithms and applications...
- Referenced in 1617 articles
- solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue ... LAPACK addresses this problem by reorganizing the algorithms to use block matrix operations, such...
- Referenced in 62 articles
- LSMR: an iterative algorithm for sparse least-squares problems. An iterative method LSMR is presented...
- Referenced in 301 articles
- combination of the CGS algorithm (a “squared” conjugate gradient method) with a preconditioning called ILLU ... competitive solver for nonsymmetric linear systems, at least for problems that are not too large...
- Referenced in 57 articles
- regularized least squares problem: A fast algorithm for sparse reconstruction based on shrinkage, subspace optimization...
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- efficient algorithms for solving linear systems of equations and linear least squares problems, in particular...
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- cyclic reduction algorithm. When the problem is singular, a least-squares solution is computed. Singularities...
- Referenced in 159 articles
- data for use in comparative studies of algorithms for numerical linear algebra. Matrices as well ... software and services, from linear systems, least squares, and eigenvalue computations in a wide variety...
- Referenced in 158 articles
- optimal trade-off between the least-squares fit and the one-norm of the solution ... root-finding algorithm for finding arbitrary points on this curve; the algorithm is suitable ... gradient-projection method approximately minimizes a least-squares problem with an explicit one-norm constraint...
- Referenced in 599 articles
- complete generality and confine our scope to algorithms that are easy to implement ... method for the solution of nonlinear least squares problems. Both, overdetermined and underdetermined nonlinear least ... used to demonstrate the behavior of optimization algorithms. Chapter 7 introduces implicit filtering, a technique...
Harwell-Boeing sparse matrix collection
- Referenced in 210 articles
- comprises problems in linear systems, least squares, and eigenvalue calculations from a wide variety ... standard benchmark for comparative studies of algorithms. The procedures for obtaining and using the test...
- Referenced in 9 articles
- interface to the Levenberg-Marquardt nonlinear least-squares algorithm found in MINPACK, plus support ... solving nonlinear least-squares problems by a modification of the Levenberg-Marquardt algorithm, with support...
- Referenced in 54 articles
- descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates...