On three-term conjugate gradient method for optimization problems with applications on COVID-19 model and robotic motion control. [PDF]
Adv Contin Discret Model, 2022 The three-term conjugate gradient (CG) algorithms are among the efficient variants of CG algorithms for solving optimization models. This is due to their simplicity and low memory requirements.
Sulaiman IM +5 more
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A new smoothing modified three-term conjugate gradient method for l1 $l_{1}$-norm minimization problem [PDF]
Journal of Inequalities and Applications, 2018 We consider a kind of nonsmooth optimization problems with l1 $l_{1}$-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems.
Shouqiang Du, Miao Chen
doaj +2 more sources
A spectral conjugate gradient method for solving large-scale unconstrained optimization
Computers and Mathematics With Applications, 2019 This paper establishes a spectral conjugate gradient method for solving unconstrained optimization problems, where the conjugate parameter and the spectral parameter satisfy a restrictive relationship.
J K Liu
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Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold [PDF]
International Conference on Learning Representations, 2023 The conjugate gradient method is a crucial first-order optimization method that generally converges faster than the steepest descent method, and its computational cost is much lower than that of second-order methods.
Jun Chen +6 more
semanticscholar +1 more source
A nonlinear conjugate gradient method with complexity guarantees and its application to nonconvex regression [PDF]
EURO Journal on Computational Optimization, 2022 Nonlinear conjugate gradients are among the most popular techniques for solving continuous optimization problems. Although these schemes have long been studied from a global convergence standpoint, their worst-case complexity properties have yet to be ...
R'emi Chan--Renous-Legoubin, C. Royer
semanticscholar +1 more source
A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
International Journal of Analysis and Applications, 2023 The conjugate gradient and Quasi-Newton methods have advantages and drawbacks, as although quasi-Newton algorithm has more rapid convergence than conjugate gradient, they require more storage compared to conjugate gradient algorithms.
Mardeen Sh. Taher, Salah G. Shareef
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A New Parameterized Conjugate Gradient Method based on Generalized Perry Conjugate Gradient Method
Tikrit Journal of Pure Science, 2023 A New Parameterized Conjugate Gradient Method based on Generalized Perry Conjugate Gradient Method is proposed to be based on Perry's idea, the descent condition and the global convergent is proven under Wolfe condition.
Khalil K. Abbo, Nazar K. Hussein
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Parallel conjugate gradient method
Lietuvos Matematikos Rinkinys, 2003 We investigate a parallel version of the preconditioned conjugate gradientmethod. A scalability analysis is done for a finite difference schemewhich approximates the 3D elliptic problem.
Raimondas Čiegis, Galina Šilko
doaj +3 more sources
Differentiating the Method of Conjugate Gradients [PDF]
SIAM Journal on Matrix Analysis and Applications, 2014 The method of conjugate gradients (CG) is widely used for the iterative solution of large sparse systems of equations $Ax=b$, where $A\in\Re^{n\times n}$ is symmetric positive definite. Let $x_k$ denote the $k$th iterate of CG. This is a nonlinear differentiable function of $b$. In this paper we obtain expressions for $J_k$, the Jacobian matrix of $x_k$
Serge Gratton +3 more
openaire +2 more sources
Comparison Between Steepest Descent Method and Conjugate Gradient Method by Using Matlab
Journal of Studies in Science and Engineering, 2021 The Steepest descent method and the Conjugate gradient method to minimize nonlinear functions have been studied in this work. Algorithms are presented and implemented in Matlab software for both methods.
Dana Taha Mohammed Salih +1 more
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