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Trust-region methods for large-scale unconstrained optimization
Philip E. Gill
Department of Mathematics, UCSD
Abstract:
We consider methods for large-scale unconstrained optimization based on finding an approximate solution of a quadratically constrained trust-region subproblem. The solver is based on sequential subspace minimization with a modified barrier "accelerator" direction in the subspace basis.
Tuesday, April 29, 2008
11:00AM AP&M 2402
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Randolph E. Bank
Philip E. Gill
Michael Holst
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Randolph E. Bank
Philip E. Gill
Michael Holst
Administrative Contact:
[ Click to Send Email ]
Philip E. Gill
Department of Mathematics, UCSD
Abstract:
We consider methods for large-scale unconstrained optimization based on finding an approximate solution of a quadratically constrained trust-region subproblem. The solver is based on sequential subspace minimization with a modified barrier "accelerator" direction in the subspace basis.
Tuesday, April 29, 2008
11:00AM AP&M 2402