A new smoothing modified three-term conjugate gradient method for l1 $l_{1}$-norm minimization problem [PDF]
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
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Dai-Kou type conjugate gradient methods with a line search only using gradient [PDF]
In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope.
Yuanyuan Huang, Changhe Liu
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A hybrid conjugate gradient algorithm for constrained monotone equations with application in compressive sensing [PDF]
Combining the projection method of Solodov and Svaiter with the Liu-Storey and Fletcher Reeves conjugate gradient algorithm of Djordjević for unconstrained minimization problems, a hybrid conjugate gradient algorithm is proposed and extended to solve ...
Abdulkarim Hassan Ibrahim +4 more
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A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
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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New modification of the hestenes-stiefel with strong wolfe line search [PDF]
. The method of the nonlinear conjugate gradient is widely used in solving large-scale unconstrained optimization since been proven in solving optimization problems without using large memory storage.
Basri, Srimazzura +2 more
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Comparison Between Steepest Descent Method and Conjugate Gradient Method by Using Matlab
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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A New Spectral Conjugate Gradient method for solving unconstrained Optimization problems [PDF]
The spectral conjugate gradient methods are fascinating, and it has been shown that they are useful for strictly convex quadratic reduction when used properly.
أسامة محمد طاهر ویس +2 more
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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 ...
Rémi Chan–Renous-Legoubin +1 more
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Anew Conjugate Gradient Algorithm Based on The (Dai-Liao) Conjugate Gradient Method
In this paper we can derive a new search direction of conjugating gradient method associated with (Dai-Liao method ) the new algorithm becomes converged by assuming some hypothesis.
SHAHER QAHTAN HUSSEIN +2 more
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A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization
The nonlinear conjugate gradient algorithms are a very effective way in solving large-scale unconstrained optimization problems. Based on some famous previous conjugate gradient methods, a modified hybrid conjugate gradient method was proposed.
Minglei Fang +3 more
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