Algorithm for inequality-constrained least squares problems
From MaRDI portal
Publication:520270
DOI10.1007/s40314-015-0226-3zbMath1359.15008OpenAlexW2079518324MaRDI QIDQ520270
Publication date: 3 April 2017
Published in: Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40314-015-0226-3
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (2)
The iterative solution of a class of tensor equations via Einstein product with a tensor inequality constraint ⋮ The least squares solution of a class of generalized Sylvester-transpose matrix equations with the norm inequality constraint
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization
- Iterative solutions to matrix equations of the form \(A_{i}XB_{i}=F_{i}\)
- Some properties of submatrices in a solution to the matrix equation \(AXB=C\) with applications
- An iterative algorithm for solving a finite-dimensional linear operator equation \(T(x)=f\) with applications
- Matrix iterative solutions to the least squares problem of \(BXA^{T} = F\) with some linear constraints
- On the symmetric solutions of linear matrix equations
- Ranks of least squares solutions of the matrix equation \(AXB=C\)
- The solutions to some operator equations
- Positive solutions to operator equations \(AXB=C\)
- Generalized reflexive solutions of the matrix equation \(AXB=D\) and an associated optimal approximation problem
- Ranks of Hermitian and skew-Hermitian solutions to the matrix equation \(AXA^*=B\)
- A new penalty function algorithm for convex quadratic programming
- An iteration method for the symmetric solutions and the optimal approximation solution of the matrix equation \(AXB\)=\(C\)
- Global minimization using an augmented Lagrangian method with variable lower-level constraints
- A minimal residual algorithm for the inconsistent matrix equation \(AXB = C\) over symmetric matrices
- Augmented Lagrangian methods under the constant positive linear dependence constraint qualification
- An iterative method for the skew-symmetric solution and the optimal approximate solution of the matrix equation \(AXB=C\)
- The reflexive solutions of the matrix equation \(AX B = C\)
- Iterative solutions of the generalized Sylvester matrix equations by using the hierarchical identification principle
- An iterative method for the least squares symmetric solution of the linear matrix equation \(AXB = C\)
- An \(O(n^ 3L)\) primal interior point algorithm for convex quadratic programming
- The boundedness of penalty parameters in an augmented Lagrangian method with constrained subproblems
- Re-nnd SOLUTIONS OF THE MATRIX EQUATION AXB=C
- On the Uniqueness of Nonnegative Sparse Solutions to Underdetermined Systems of Equations
- Iterative orthogonal direction methods for Hermitian minimum norm solutions of two consistent matrix equations
- A quadratic programming algorithm
- Numerical Optimization
- Nonmonotone Spectral Projected Gradient Methods on Convex Sets
- Necessary and sufficient conditions for quadratic minimality
This page was built for publication: Algorithm for inequality-constrained least squares problems
