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• W4300705949 abstract "Memoryless quasi-Newton methods are studied for solving large-scale unconstrained optimization problems. Nakayama et al. (2017) proposed a memoryless quasi-Newton method based on the spectral-scaling Broyden family and showed that the method satisfies the sufficient descent condition and converges globally. To relax the conditions on parameters in the method, we apply the modification technique by Kou and Dai (2015) to the method of Nakayama et al., and we give a hybrid method of the three-term conjugate gradient method and the memoryless quasi-Newton method based on the spectral-scaling Broyden family. We show that our method satisfies the sufficient descent condition, and we prove that the method converges globally. Furthermore, we give a concrete choice of parameters for our method. Finally, some numerical results are given." @default.
• W4300705949 created "2022-10-04" @default.
• W4300705949 creator A5002569473 @default.
• W4300705949 date "2018-06-01" @default.
• W4300705949 modified "2023-10-15" @default.
• W4300705949 title "A hybrid method of three-term conjugate gradient method and memoryless quasi-Newton method for unconstrained optimization" @default.
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• W4300705949 doi "https://doi.org/10.55937/sut/1547386572" @default.
• W4300705949 hasPublicationYear "2018" @default.
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