Voir la notice de l'article provenant de la source Czech Digital Mathematics Library
Lukšan, Ladislav. Inexact trust region method for large sparse nonlinear least squares. Kybernetika, Tome 29 (1993) no. 4, pp. 305-324. http://geodesic.mathdoc.fr/item/KYB_1993_29_4_a0/
@article{KYB_1993_29_4_a0,
author = {Luk\v{s}an, Ladislav},
title = {Inexact trust region method for large sparse nonlinear least squares},
journal = {Kybernetika},
pages = {305--324},
year = {1993},
volume = {29},
number = {4},
mrnumber = {1247880},
zbl = {0806.65060},
language = {en},
url = {http://geodesic.mathdoc.fr/item/KYB_1993_29_4_a0/}
}
[1] G. Golub, W. Kahan: Calculating the singular values and pseudo-inverse of a matrix. SIAM J. Numer. Anal. 2 (1965), 205-224. | MR | Zbl
[2] J. J. More B. S. Garbow, K. E. Hillstrom: Testing unconstrained optimization software. ACM Trans. Math. Software 7 (1981), 17-41. | MR
[3] J. E. Dennis, H. H. W. Mei: An Unconstrained Optimization Algorithm which Uses Function and Gradient Vlues. Report No. TR-75-246. Dept. of Computer Sci., Cornell University 1975.
[4] C. C. Paige: Bidiagonalization of matrices and solution of linear equations. SIAM J. Numer. Anal. 11 (1974), 197-209. | MR | Zbl
[5] C. C. Paige, M. A. Saunders: LSQR: An algorithm for sparse linear equations and sparse least squares. ACM Trans. Math. Software 8 (1982), 43-71. | MR | Zbl
[6] M. J. D. Powell: Convergence properties of a class of minimization algoritms. In: Non-linear Programming 2 (O. L. Mangasarian, R. R. Meyer and S. M. Robinson, eds.), Academic Press, London 1975. | MR
[7] G. A. Shultz R. B. Schnabel, R. H. Byrd: A family of trust-region-based algorithms for unconstrained minimization with strong global convergence properties. SIAM J. Numer. Anal. 22 (1985), 47-67. | MR
[8] T. Steihaug: The conjugate gradient method and trust regions in large-scale optimization. SIAM J. Numer. Anal. 20 (1983), 626-637. | MR | Zbl