無制約最適化問題に対するメモリーレス準ニュートン法について  [in Japanese] Memoryless Quasi-Newton Methods for Unconstrained Optimization  [in Japanese]

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Abstract

<p>Recently, particular attention has been paid attention to memoryless quasi-Newton methods for solving unconstrained optimization problems. Because memoryless quasi-Newton methods do not need the storage of memories for matrix and their computing cost par a iteration is low, the methods are efficient to large-scale unconstrained optimization problems. Moreover, since the methods are closely related to not only quasi-Newton methods but also nonlinear conjugate gradient methods and nonlinear three-term conjugate gradient method, it is expected that the methods are promising. This paper introduces recent studies on memoryless quasi-Newton methods.</p>

Journal

  • Bulletin of the Japan Society for Industrial and Applied Mathematics

    Bulletin of the Japan Society for Industrial and Applied Mathematics 29(4), 8-17, 2019

    The Japan Society for Industrial and Applied Mathematics

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