38 citations · 242 across the 36 of their papers we have counts for
37 papers
ResQPASS: an algorithm for bounded variable linear least squares with asymptotic Krylov convergence
Bas Symoens, Wim Vanroose
We present the Residual Quadratic Programming Active-Set Subspace (ResQPASS) method that solves large-scale linear least-squares problems with bound constraints on the variables. T…
Convergence analysis of a regularized inexact interior-point method for linear programming problems
Jeffrey Cornelis, Wim Vanroose
Interior-point methods for linear programming problems require the repeated solution of a linear system of equations. Solving these linear systems is non-trivial due to the severe…
Sequential Projected Newton method for regularization of nonlinear least squares problems
Jeffrey Cornelis, Wim Vanroose
We develop a computationally efficient algorithm for the automatic regularization of nonlinear inverse problems based on the discrepancy principle. We formulate the problem as an e…
Krylov-Simplex method that minimizes the residual in -norm or -norm
Wim Vanroose, Jeffrey Cornelis
The paper presents two variants of a Krylov-Simplex iterative method that combines Krylov and simplex iterations to minimize the residual . The first method minimizes $\|…
Projected Newton method for noise constrained regularization
Jeffrey Cornelis, Wim Vanroose
Choosing an appropriate regularization term is necessary to obtain a meaningful solution to an ill-posed linear inverse problem contaminated with measurement errors or noise. The $…
Projected Newton Method for noise constrained Tikhonov regularization
Jeffrey Cornelis, Nick Schenkels, Wim Vanroose
Tikhonov regularization is a popular approach to obtain a meaningful solution for ill-conditioned linear least squares problems. A relatively simple way of choosing a good regulari…