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首页> 外文期刊>Journal of Optimization Theory and Applications >Nonsmooth Steepest Descent Method by Proximal Subdifferentials in Hilbert Spaces
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Nonsmooth Steepest Descent Method by Proximal Subdifferentials in Hilbert Spaces

机译:Hilbert空间中近次微分的非光滑最陡下降法

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摘要

In this paper, we first study a nonsmooth steepest descent method for nonsmooth functions defined on a Hilbert space and establish the corresponding algorithm by proximal subgradients. Then, we use this algorithm to find stationary points for those functions satisfying prox-regularity and Lipschitz continuity. As an application, the established algorithm is used to search for the minimizer of a lower semicontinuous and convex function on a finite-dimensional space. A convergence theorem, as an extension and improvement of the existing converging result for twice continuously differentiable convex functions, is also presented therein.
机译:在本文中,我们首先研究了针对希尔伯特空间上定义的非光滑函数的非光滑最速下降方法,并通过近端次梯度建立了相应的算法。然后,我们使用此算法为那些满足近似正则性和Lipschitz连续性的函数找到固定点。作为一种应用,已建立的算法用于在有限维空间上搜索下半连续凸函数的极小值。其中还提出了收敛定理,作为对两次连续可微凸函数的现有收敛结果的扩展和改进。

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