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Hugo de la

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A Minimal-Gradient Subspace Method for Unconstrained Optimization

A minimal-gradient subspace method for unconstrained optimization of SPD quadratics, which attains the highest success count, whereas L-BFGS requires fewer median gradient evaluations and less CPU time.

Oscar Dalmau, Hugo de la, Cruz Cansino · 0 citations