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A Hybrid of DL and WYL Nonlinear Conjugate Gradient Methods
Abstract and Applied Analysis, 2014 The conjugate gradient method is an efficient method for solving large-scale nonlinear optimization problems. In this paper, we propose a nonlinear conjugate gradient method which can be considered as a hybrid of DL and WYL conjugate gradient methods ...
Shengwei Yao, Bin Qin
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Several Guaranteed Descent Conjugate Gradient Methods for Unconstrained Optimization
Journal of Applied Mathematics, 2014 This paper investigates a general form of guaranteed descent conjugate gradient methods which satisfies the descent condition gkTdk≤-1-1/4θkgk2 θk>1/4 and which is strongly convergent whenever the weak Wolfe line search is fulfilled.
San-Yang Liu, Yuan-Yuan Huang
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The new spectral conjugate gradient method for large-scale unconstrained optimisation
Journal of Inequalities and Applications, 2020 The spectral conjugate gradient methods are very interesting and have been proved to be effective for strictly convex quadratic minimisation. In this paper, a new spectral conjugate gradient method is proposed to solve large-scale unconstrained ...
Li Wang +3 more
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Two new spectral conjugate gradient algorithms based on Hestenes–Stiefel
Journal of Algorithms & Computational Technology, 2017 The spectral conjugate gradient algorithm, which is a variant of conjugate gradient method, is one of the effective methods for solving unconstrained optimization problems.
Guofang Wang +4 more
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Numerical: Jurnal Matematika dan Pendidikan Matematika, 2020 This paper develops a Neural network (NN) using conjugate gradient (CG). The modification of this method is in defining the direction of linear search.
Azwar Riza Habibi +2 more
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Algorithms, 2021 The conjugate gradient method is one of the most popular methods to solve large-scale unconstrained optimization problems since it does not require the second derivative, such as Newton’s method or approximations.
Zabidin Salleh +3 more
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The conjugate gradient method [PDF]
The Leading Edge, 2018 The conjugate gradient method can be used to solve many large linear geophysical problems — for example, least-squares parabolic and hyperbolic Radon transform, traveltime tomography, least-squares migration, and full-waveform inversion (FWI) (e.g., Witte et al., 2018).
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Symmetric Perry conjugate gradient method [PDF]
Computational Optimization and Applications, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dongyi Liu, Genqi Xu
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The Limited Memory Conjugate Gradient Method [PDF]
SIAM Journal on Optimization, 2013 In theory, the successive gradients generated by the conjugate gradient method applied to a quadratic should be orthogonal. However, for some ill-conditioned problems, orthogonality is quickly lost due to rounding errors, and convergence is much slower than expected. A limited memory version of the nonlinear conjugate gradient method is developed.
William W. Hager, Hongchao Zhang
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Two Versions of the Spectral Nonlinear Conjugate Gradient Method
Al-Mustansiriyah Journal of Science, 2018 The nonlinear conjugate gradient method is widely used to solve unconstrained optimization problems. In this paper the development of different versions of nonlinear conjugate gradient methods with global convergence properties proved.
Basim A. Hassan, Haneen A. Alashoor
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