Recent Advances in Gradient Based Unconstrained Optimization Techniques for Large Problems

Abstract

The paper surveys recent results in conjugate gradient methods, variable storage variable metric methods, sparse variable metric and finite difference Newton methods, and truncated Newton methods. Both computational and theoretical results will be discussed, as well as currently distributed software.