AbstractWe propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai and Borwein (BB) method and analyze the convergence properties of this new descent method. Motivated by the fact that BB method does not guarantee descent in the objective function at each iteration, but performs better than the steepest descent method, we therefore attempt to find stepsize formula which enables us to approximate the Hessian based on the Quasi-Cauchy equation and possess monotone property in each iteration. Practical insights on the effectiveness of the proposed techniques are given by a numerical comparison with the BB method
In this paper, we propose a new non-monotone conjugate gradient method for solving unconstrained non...
The success of Newton’s method for smooth optimization, when Hessians are available, motivated the i...
AbstractAn algorithm for solving nonlinear monotone equations is proposed, which combines a modified...
We propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai and Borw...
AbstractWe propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai ...
ABSTRACT In this paper we propose new globalization strategies for the Barzilai and Borwein gradient...
The focus of this thesis is on finding the unconstrained minimizer of a function. Specifically, we ...
AbstractIn this paper, we propose some improvements on a new gradient-type method for solving large-...
In this paper we present a new algorithm of steepest descent type. A new technique for steplength co...
In this work we develop a new gradient-type method with improved Hessian approximation for unconstra...
In this paper, we propose some improvements on a new gradient-type method for solving large-scale un...
The Barzilai and Borwein gradient algorithm has received a great deal of attention in recent decades...
The focus of the thesis is on finding the unconstrained minimizer of a function by using the fixed s...
The focus of this thesis is on finding the unconstrained minimizer of a function by using the alter...
We address composite optimization problems, which consist in minimizing the sum of a smooth and a me...
In this paper, we propose a new non-monotone conjugate gradient method for solving unconstrained non...
The success of Newton’s method for smooth optimization, when Hessians are available, motivated the i...
AbstractAn algorithm for solving nonlinear monotone equations is proposed, which combines a modified...
We propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai and Borw...
AbstractWe propose a new monotone algorithm for unconstrained optimization in the frame of Barzilai ...
ABSTRACT In this paper we propose new globalization strategies for the Barzilai and Borwein gradient...
The focus of this thesis is on finding the unconstrained minimizer of a function. Specifically, we ...
AbstractIn this paper, we propose some improvements on a new gradient-type method for solving large-...
In this paper we present a new algorithm of steepest descent type. A new technique for steplength co...
In this work we develop a new gradient-type method with improved Hessian approximation for unconstra...
In this paper, we propose some improvements on a new gradient-type method for solving large-scale un...
The Barzilai and Borwein gradient algorithm has received a great deal of attention in recent decades...
The focus of the thesis is on finding the unconstrained minimizer of a function by using the fixed s...
The focus of this thesis is on finding the unconstrained minimizer of a function by using the alter...
We address composite optimization problems, which consist in minimizing the sum of a smooth and a me...
In this paper, we propose a new non-monotone conjugate gradient method for solving unconstrained non...
The success of Newton’s method for smooth optimization, when Hessians are available, motivated the i...
AbstractAn algorithm for solving nonlinear monotone equations is proposed, which combines a modified...