Several accelerated subspace minimization conjugate gradient methods based on regularization model and convergence rate analysis for nonconvex problems
Author:
Funder
National Natural Science Foundation of China
Guangxi Natural Science Foundation
Natural Science Basic Research Program of Shaanxi
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics
Link
https://link.springer.com/content/pdf/10.1007/s11075-022-01319-6.pdf
Reference43 articles.
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3. Barzilai, J., Borwein, J.M.: Two-point step size gradient methods. IMA J. Numer. Anal. 8, 141–148 (1988)
4. Bellavia, S., Morini, B., Cartis, C., Gould, N.I.M., Toint, Ph.L.: Convergence of a regularizedeuclidean residual algorithm for nonlinear least-squares. SIAM J. Numer. Anal. 48, 1–29 (2010)
5. Bellavia, S., Morini, B.: Strong local convergence properties of adaptive regularized methodsfor nonlinear least squares. IMA J. Numer. Anal. 35, 947–968 (2014)
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