This paper relates some numerical experiments with variable storage quasi-Newton methods for the optimization of large-scale models. The basic idea of the recommended algorithm is to start bfgs updates on a diagonal matrix, itself generated by an update formula and adjusted to Rayleigh's ellipsoid of the local Hessian of the objective function in the direction of the change in the gradient. A variational derivation of some rank one and rank two updates in Hilbert spaces is also given.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.