实阶总变分与学习方案中损失函数的应用

IF 1.2 2区 数学 Q1 MATHEMATICS
Pan Liu, Xin Yang Lu, Kunlun He
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引用次数: 0

摘要

损失函数是现代数据驱动方法的重要组成部分,如双级训练方案和机器学习。在本文中,我们提出了一个由[公式:见文]-阶(an)-各向同性全变分半模[公式:见文],[公式:见文]组成的损失函数,通过Riemann-Liouville (RL)分数阶导数来定义。我们重点研究了这类损失函数的关键理论性质,如关于函数和导数阶的下半连续性和紧性[公式:见文本]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real order total variation with applications to the loss functions in learning schemes
Loss functions are an essential part in modern data-driven approaches, such as bi-level training scheme and machine learnings. In this paper, we propose a loss function consisting of a [Formula: see text]-order (an)-isotropic total variation semi-norms [Formula: see text], [Formula: see text], defined via the Riemann–Liouville (RL) fractional derivative. We focus on studying key theoretical properties, such as the lower semi-continuity and compactness with respect to both the function and the order of derivative [Formula: see text], of such loss functions.
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来源期刊
CiteScore
2.90
自引率
6.20%
发文量
78
审稿时长
>12 weeks
期刊介绍: With traditional boundaries between various specialized fields of mathematics becoming less and less visible, Communications in Contemporary Mathematics (CCM) presents the forefront of research in the fields of: Algebra, Analysis, Applied Mathematics, Dynamical Systems, Geometry, Mathematical Physics, Number Theory, Partial Differential Equations and Topology, among others. It provides a forum to stimulate interactions between different areas. Both original research papers and expository articles will be published.
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