This work is a survey on the methods for large scale unconstrained optimization. Besides its own theoretical importance, the growing interest in the last years in solving problems with a larger and larger number of variables are arising very frequently from real world as a result of modeling systems with a very complex structure. In this paper the main methods for solving large scale unconstrained optimization problems are briefly described and an accurate choice of references is reported
An unconstrained minimizer of a general nonlinear function may be found by solving a sequence of con...
On February 15-17, 1993, a conference on Large Scale Optimization, hosted by the Center for Applied ...
AbstractRecent results on the solution of large, banded or sparse systems and on global unconstraine...
We propose an optimal control approach to tackle large scale unconstrained optimization problems. Ou...
In this article, we review methods for the solution of unconstrained optimization problems, where t...
We give an introductory overview of the field of large-scale numerical optimization; some of the ba...
The recent explosion in size and complexity of datasets and the increased availability of computatio...
This volume provides resourceful thinking and insightful management solutions to the many challenges...
Finding the unconstrained minimizer of a function of more than one variable is an important problem ...
In this book, theory of large scale optimization is introduced with case studies of real-world probl...
Abstract. In this paper, an unconstrained minimization algorithm is defined in which a nonmonotone l...
In this paper we define globally convergent algorithms for the solution of large dimensional unconst...
Although it is a very old theme, unconstrained optimization is an area which is always actual for ma...
A large scale unconstrained optimization problem can be formulated when the dimension n is large. Th...
A preconditioned steepest descent (SD) method for solving very large (with dimensions up to 106 ) un...
An unconstrained minimizer of a general nonlinear function may be found by solving a sequence of con...
On February 15-17, 1993, a conference on Large Scale Optimization, hosted by the Center for Applied ...
AbstractRecent results on the solution of large, banded or sparse systems and on global unconstraine...
We propose an optimal control approach to tackle large scale unconstrained optimization problems. Ou...
In this article, we review methods for the solution of unconstrained optimization problems, where t...
We give an introductory overview of the field of large-scale numerical optimization; some of the ba...
The recent explosion in size and complexity of datasets and the increased availability of computatio...
This volume provides resourceful thinking and insightful management solutions to the many challenges...
Finding the unconstrained minimizer of a function of more than one variable is an important problem ...
In this book, theory of large scale optimization is introduced with case studies of real-world probl...
Abstract. In this paper, an unconstrained minimization algorithm is defined in which a nonmonotone l...
In this paper we define globally convergent algorithms for the solution of large dimensional unconst...
Although it is a very old theme, unconstrained optimization is an area which is always actual for ma...
A large scale unconstrained optimization problem can be formulated when the dimension n is large. Th...
A preconditioned steepest descent (SD) method for solving very large (with dimensions up to 106 ) un...
An unconstrained minimizer of a general nonlinear function may be found by solving a sequence of con...
On February 15-17, 1993, a conference on Large Scale Optimization, hosted by the Center for Applied ...
AbstractRecent results on the solution of large, banded or sparse systems and on global unconstraine...