Detecting negative eigenvalues of exact and approximate Hessian matrices in optimization-Reference-Cited by-同舟云学术

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Detecting negative eigenvalues of exact and approximate Hessian matrices in optimization

Published:2023-07-05 Issue:8 Volume:17 Page:1739-1756
ISSN:1862-4472
Container-title:Optimization Letters
language:en
Short-container-title:Optim Lett

Author:

Hare Warren,Royer Clément W.^ORCID

Funder

NSERC

Agence Nationale pour la Recherche

France Canada Research Fund

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization,Business, Management and Accounting (miscellaneous)

Link

https://link.springer.com/content/pdf/10.1007/s11590-023-02033-5.pdf

Reference21 articles.

1. Goldfarb, D.: Curvilinear path steplength algorithms for minimization which use directions of negative curvature. Math. Program. 18, 31–40 (1980)

2. McCormick, G.P.: A modification of Armijo step-size rule for negative curvature. Math. Program. 13, 111–115 (1977)

3. Moré, J.J., Sorensen, D.C.: On the use of directions of negative curvature in a modified Newton method. Math. Program. 16, 1–20 (1979)

4. Cartis, C., Gould, N.I.M., Toint, P.L.: Complexity bounds for second-order optimality in unconstrained optimization. J. Complex. 28, 93–108 (2012)

5. Curtis, F.E., Lubberts, Z., Robinson, D.P.: Concise complexity analyses for trust region methods. Optim. Lett. 12, 1713–1724 (2018)

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