Numerical Experiences with New Truncated Newton Methodsin Large Scale Unconstrained Optimization
作者： Stefano Lucidi , Massimo Roma
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摘要: Recently, in [12] a very general class of truncated Newton methods has been proposed for solving large scale unconstrained optimization problems. In this work we present the results an extensive numerical experience obtained by different algorithms which belong to preceding class. This study, besides investigating are best algorithmic choices approach, clarifies some significant points underlies every based algorithm.
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