Least squares problems with inequality constraints as quadratic constraints
From MaRDI portal
Publication:848575
DOI10.1016/j.laa.2009.04.017zbMath1185.65068OpenAlexW2088022161MaRDI QIDQ848575
Rosemary A. Renaut, Jodi L. Mead
Publication date: 4 March 2010
Published in: Linear Algebra and its Applications (Search for Journal in Brave)
Full work available at URL: https://scholarworks.boisestate.edu/cgi/viewcontent.cgi?article=1015&context=math_facpubs
algorithmregularizationnumerical examplesbox constraintsmaximum a posteriori estimationlinear least squaresill-posed inverse problemsquadratic constraint
Numerical solutions to overdetermined systems, pseudoinverses (65F20) Ill-posedness and regularization problems in numerical linear algebra (65F22)
Related Items
Computational and sensitivity aspects of eigenvalue-based methods for the large-scale trust-region subproblem ⋮ \(\ell^1\)-analysis minimization and generalized (co-)sparsity: when does recovery succeed? ⋮ A dual estimator as a tool for solving regression problems ⋮ \( \chi^2\) test for total variation regularization parameter selection ⋮ General Error Estimates for the Longstaff–Schwartz Least-Squares Monte Carlo Algorithm
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On iterative algorithms for linear least squares problems with bound constraints
- Solving the minimal least squares problem subject to bounds on the variables
- Global optimization by multilevel coordinate search
- Regularization tools: A Matlab package for analysis and solution of discrete ill-posed problems
- Bounded-variable least-squares: an algorithm and applications
- An iterative method for linear discrete ill-posed problems with box constraints
- A Trust-Region Approach to the Regularization of Large-Scale Discrete Forms of Ill-Posed Problems
- A priori weighting for parameter estimation
- A Newton root-finding algorithm for estimating the regularization parameter for solving ill-conditioned least squares problems
- Constrained Least Squares Interval Estimation
- Numerical Optimization
- Newton's Method for Large Bound-Constrained Optimization Problems
- Extensions and Applications of the Householder Algorithm for Solving Linear Least Squares Problems