The Joint Bidiagonalization Method for Large GSVD Computations in Finite Precision
Author:
Affiliation:
1. Department of Mathematical Sciences, Tsinghua University, 100084 Beijing, People‘s Republic of China.
Funder
National Natural Science Foundation of China
Publisher
Society for Industrial & Applied Mathematics (SIAM)
Subject
Analysis
Reference30 articles.
1. Reorthogonalization for the Golub–Kahan–Lanczos bidiagonal reduction
2. Matrix Computations
3. Accuracy and Stability of Numerical Algorithms
4. Two Harmonic Jacobi–Davidson Methods for Computing a Partial Generalized Singular Value Decomposition of a Large Matrix Pair
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1. A Preconditioned Krylov Subspace Method for Linear Inverse Problems with General-Form Tikhonov Regularization;SIAM Journal on Scientific Computing;2024-08-14
2. Thick-restarted joint Lanczos bidiagonalization for the GSVD;Journal of Computational and Applied Mathematics;2024-04
3. The Joint Bidiagonalization of a Matrix Pair with Inaccurate Inner Iterations;SIAM Journal on Matrix Analysis and Applications;2024-01-17
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