Estimation of the \(L\)-curve via Lanczos bidiagonalization
From MaRDI portal
Publication:1963908
DOI10.1023/A:1022383005969zbMath0945.65044MaRDI QIDQ1963908
Gene H. Golub, Daniela Calvetti, Lothar Reichel
Publication date: 5 October 2000
Published in: BIT (Search for Journal in Brave)
regularization\(L\)-curve\(L\)-ribbonpartial Lanczos bidiagonalizationill-conditioned systems of linear equations
Related Items (50)
Some matrix nearness problems suggested by Tikhonov regularization ⋮ RBF approximation of three dimensional PDEs using tensor Krylov subspace methods ⋮ Sylvester Tikhonov-regularization methods in image restoration ⋮ A Hybrid LSMR Algorithm for Large-Scale Tikhonov Regularization ⋮ Greedy Tikhonov regularization for large linear ill-posed problems ⋮ The regularizing effect of the Golub-Kahan iterative bidiagonalization and revealing the noise level in the data ⋮ Tensor Krylov subspace methods via the Einstein product with applications to image and video processing ⋮ Lanczos tridiagonalization and core problems ⋮ Golub-Kahan vs. Monte Carlo: a comparison of bidiagonlization and a randomized SVD method for the solution of linear discrete ill-posed problems ⋮ The block Lanczos algorithm for linear ill-posed problems ⋮ A fast truncated Lagrange method for large-scale image restoration problems ⋮ An iterative Lagrange method for the regularization of discrete ill-posed inverse problems ⋮ Large-scale Tikhonov regularization via reduction by orthogonal projection ⋮ Krylov methods for inverse problems: Surveying classical, and introducing new, algorithmic approaches ⋮ A Bayesian interpretation of the L-curve ⋮ Minimization of functionals on the solution of a large-scale discrete ill-posed problem ⋮ Efficient determination of the hyperparameter in regularized total least squares problems ⋮ Old and new parameter choice rules for discrete ill-posed problems ⋮ Some results on the regularization of LSQR for large-scale discrete ill-posed problems ⋮ Seismic wavefield redatuming with regularized multi-dimensional deconvolution ⋮ A new method for solving linear ill-posed problems ⋮ GKB-FP: An algorithm for large-scale discrete ill-posed problems ⋮ A preconditioned multiple shooting shadowing algorithm for the sensitivity analysis of chaotic systems ⋮ A new \(L\)-curve for ill-posed problems ⋮ The Lagrange method for the regularization of discrete ill-posed problems ⋮ Discrete cosine transform LSQR and GMRES methods for multidimensional ill-posed problems ⋮ Analysis of directed networks via partial singular value decomposition and Gauss quadrature ⋮ Conditional gradient Tikhonov method for a convex optimization problem in image restoration ⋮ Regula falsi based automatic regularization method for PDE constrained optimization ⋮ Convex constrained optimization for large-scale generalized Sylvester equations ⋮ Lanczos based preconditioner for discrete ill-posed problems ⋮ A new variant of L-curve for Tikhonov regularization ⋮ An algorithm for image denoising with automatic noise estimate ⋮ Regularization parameter determination for discrete ill-posed problems ⋮ A global Lanczos method for image restoration ⋮ A survey on variational characterizations for nonlinear eigenvalue problems ⋮ Error estimates for large-scale ill-posed problems ⋮ GCV for Tikhonov regularization via global Golub–Kahan decomposition ⋮ Tikhonov regularization with MTRSVD method for solving large-scale discrete ill-posed problems ⋮ Projected Newton method for noise constrained Tikhonov regularization ⋮ Unnamed Item ⋮ A computable error bound for matrix functionals ⋮ A Framework for Regularization via Operator Approximation ⋮ Tikhonov regularization and the L-curve for large discrete ill-posed problems ⋮ A regularizing L-curve Lanczos method for underdetermined linear systems ⋮ Color image and video restoration using tensor CP decomposition ⋮ Square regularization matrices for large linear discrete ill-posed problems ⋮ Large scale least squares scattered data fitting ⋮ The triangle method for finding the corner of the L-curve ⋮ An efficient Gauss-Newton algorithm for solving regularized total least squares problems
This page was built for publication: Estimation of the \(L\)-curve via Lanczos bidiagonalization