An Overview of Some Practical Quasi-Newton Methods for Unconstrained Optimization

Abstract

Quasi-Newton methods are among the most practical and efficient iterative methods for solving unconstrained minimization problems. In this paper we give an overview of some of these methods with focus primarily on the Hessian approximation updates and modifications aimed at improving their performance.