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Accelerated Sparse Recovery via Gradient Descent with Nonlinear Conjugate Gradient Momentum
This paper applies an idea of adaptive momentum for the nonlinear conjugate gradient to accelerate optimization problems in sparse recovery....
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An accelerated conjugate gradient method with adaptive two-parameter with applications in image restoration
This paper proposes an adaptive two-parameter accelerated conjugate gradient method, which satisfies the sufficient descent condition in the search...
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A Class of Accelerated Subspace Minimization Conjugate Gradient Methods
The subspace minimization conjugate gradient methods based on Barzilai–Borwein method (SMCG_BB) and regularization model (SMCG_PR), which were...
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Two modified conjugate gradient methods for unconstrained optimization with applications in image restoration problems
The conjugate gradient methods (CGMs) are very effective iterative methods for solving unconstrained optimization problems. In this paper, the second...
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A conjugate gradient algorithm without Lipchitz continuity and its applications
An improved conjugate gradient algorithm is proposed that does not rely on the line search rule and automatically achieves sufficient descent and...
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Two sufficient descent spectral conjugate gradient algorithms for unconstrained optimization with application
This study introduces a new modification of the conjugate gradient (CG) method (IMRMIL). Additionally, two spectral CG algorithms (SCG1 and SCG2) are...
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Descent three-term DY-type conjugate gradient methods for constrained monotone equations with application
As it is known that, not all conjugate gradient (CG) methods satisfy descent property, a necessary condition for attaining global convergence result....
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Mixed-precision conjugate gradient algorithm using the groupwise update strategy
The conjugate gradient (CG) method is the most basic iterative solver for large sparse symmetric positive definite linear systems. In finite...
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Spectral Gradient Methods
In this chapter we report some basic results on a class of gradient methods for minimizing smooth functions, known as spectral gradient methods,...
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A new hybrid conjugate gradient algorithm based on the Newton direction to solve unconstrained optimization problems
In this paper, we propose a new hybrid conjugate gradient method to solve unconstrained optimization problems. This new method is defined as a convex...
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An inertial Fletcher–Reeves-type conjugate gradient projection-based method and its spectral extension for constrained nonlinear equations
In this paper, we initially enhance the Fletcher–Reeves (FR) conjugate parameter through a shrinkage multiplier, leading to a derivative-free...
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Sufficient Descent Riemannian Conjugate Gradient Methods
This paper considers sufficient descent Riemannian conjugate gradient methods with line search algorithms. We propose two kinds of sufficient descent...
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Conjugate Gradients
We begin our development of scalable algorithms for contact problems by the description of the conjugate gradient method for an unconstrained...
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A mini-batch stochastic conjugate gradient algorithm with variance reduction
Stochastic gradient descent method is popular for large scale optimization but has slow convergence asymptotically due to the inherent variance. To...
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A family of accelerated hybrid conjugate gradient method for unconstrained optimization and image restoration
In this paper, a family of hybrid conjugate parameters with restart procedure is proposed. In which, we design a hybrid conjugate parameter by using...
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Two Improved Nonlinear Conjugate Gradient Methods with the Strong Wolfe Line Search
Two improved nonlinear conjugate gradient methods are proposed by using the second inequality of the strong Wolfe line search. Under usual...
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Two Descent Dai-Yuan Conjugate Gradient Methods for Systems of Monotone Nonlinear Equations
In this paper, we present two Dai-Yuan type iterative methods for solving large-scale systems of nonlinear monotone equations. The methods can be...
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Convergence Rate of Gradient-Concordant Methods for Smooth Unconstrained Optimization
The article discusses the class of gradient-concordant numerical methods for smooth unconstrained minimization where the descent direction is...
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An improved spectral conjugate gradient projection method for monotone nonlinear equations with application
In this paper, we propose an enhanced spectral conjugate gradient (CG) projection method for solving monotone nonlinear equations with application in...
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A modified HZ conjugate gradient algorithm without gradient Lipschitz continuous condition for non convex functions
As we know, conjugate gradient methods are widely used for unconstrained optimization because of the advantages of simple structure and small...
