Add to ORKGFor unconstrained optimization, the two-point stepsize gradient method was shown to prefer over the classical steepest descent method both in theory and in real computations. In this paper..
This paper deals with gradient methods for minimizing n-dimensional strictly convex quadratic functi...
This paper deals with gradient methods for minimizing n-dimensional strictly convex quadratic functi...
The steepest descent method has a rich history and is one of the simplest and best known methods for...
We derive two-point step sizes for the steepest-descent method by approximating the secant equation....
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
It is well known that the minimization of a smooth function f (x) is equivalent to minimizing its gr...
Steepest descent method is a simple gradient method for optimization. This method has a slow converg...
In this paper, we propose some improvements on a new gradient-type method for solving large-scale un...
It is widely accepted that the stepsize is of great significance to gradient method. An efficient gr...
This paper deals with gradient methods for minimizing n-dimensional strictly convex quadratic functi...
This paper deals with gradient methods for minimizing n-dimensional strictly convex quadratic functi...
This paper deals with gradient methods for minimizing n-dimensional strictly convex quadratic functi...
The steepest descent method has a rich history and is one of the simplest and best known methods for...
We derive two-point step sizes for the steepest-descent method by approximating the secant equation....
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
The seminal paper by Barzilai and Borwein (1988) has given rise to an extensive investigation, leadi...
It is well known that the minimization of a smooth function f (x) is equivalent to minimizing its gr...
Steepest descent method is a simple gradient method for optimization. This method has a slow converg...
In this paper, we propose some improvements on a new gradient-type method for solving large-scale un...
It is widely accepted that the stepsize is of great significance to gradient method. An efficient gr...
This paper deals with gradient methods for minimizing n-dimensional strictly convex quadratic functi...
This paper deals with gradient methods for minimizing n-dimensional strictly convex quadratic functi...
This paper deals with gradient methods for minimizing n-dimensional strictly convex quadratic functi...
The steepest descent method has a rich history and is one of the simplest and best known methods for...