New Variable Metric Methods for Unconstrained Minimization Covering the Large-Scale Case

A new family of numerically efficient variable metric or quasi-Newton methods for unconstrained minimization are given, which give simple possibility of adaptation for large-scale optimization. Global convergence of the methods can be established for convex sufficiently smooth functions. Some encouraging numerical experience is reported.

Citation

Report V876, Institute of Computer Science, AV CR, Pod Vodarenskou Vezi 2, 18207 Praha 8, Czech Republic. Last revision: November 2002.

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