"Large Scale Unconstrained Optimization "
The State of the Art in Numerical Analysis, pp. 311-338,
eds: A. Watson and I. Duff, (1997) Oxford University Press.
This paper reviews advances in Newton, quasi-Newton and conjugate gradient methods for large scale optimization. It also describes several packages developed during the last ten years, and illustrates their performance on some practical problems. Much attention is given to the concept of partial separability which is gaining importance with the arrival of automatic differentiation tools and of optimization software that fully exploits its properties.