2 Strongly convexity的定义 这里介绍\alpha-strongly convex的概念。 如果一个函数f被称为\alpha-strongly convex,那么:g(x) = f(x) - \frac{\alpha}{2} ||x||_2^2是凸函数。 基于上述定义,可以衍生出一系列结论:(推导过程和\alpha-smooth类似) ...
Strong-Convexity 强凸性多用在优化中(Optimization),特别是保证很多基于梯度下降方法的算法的线形收敛速率的条件之一。 定义 一个可微函数强凸的定义是: f(y)≥f(x)+∇f(x)T(y−x)+u2∥y−x∥2f(y)≥f(x)+∇f(x)T(y−x)+u2‖y−x‖2 值得注意的是,强凸性并不要求函数处处可微(diff...
1) strong-convexity for a preference preordering 偏好预序关系的强凸性 2) weak-convexity for a preference preordering 偏好预序关系的弱凸性 3) convexity for a preference preordering 偏好预序关系的凸性 4) continuity for a preference preordering ...
In view of strong convexity, 青云英语翻译 请在下面的文本框内输入文字,然后点击开始翻译按钮进行翻译,如果您看不到结果,请重新翻译! 翻译结果1翻译结果2翻译结果3翻译结果4翻译结果5 翻译结果1复制译文编辑译文朗读译文返回顶部 强凸, 翻译结果2复制译文编辑译文朗读译文返回顶部...
But for a strong convex function, we can prove it naturally meets the PL condition and the convex parameter is just the PL parameter . strong convexity Here we assume the object funtion issmoothandone-order differentiable. We try to take minimization of the both side of the second inequality...
We demonstrate that not all strongly convex functionals are radially unbounded. Moreover, the only exceptions must be unbounded below in every neighborhood; hence, such exceptions are interesting in optimization only in that they have no local minimaAdditional informationAuthor informationJonathan Baker...
We extend strong O-convexity to higher dimensions and discuss its basic properties (Sect. 6.1). Then, we characterize strongly O-convex flats and derive a condition for the equivalence of two orientation sets (Sect. 6.2). Finally, we study strongly O-convex halfspaces and characterize strongly...
1) near strong convexity 近强凸 1. In this paper, we discusses the strong convexity, very convexity, near strong convexity, extremal convexity and (w) property, and the results generalize the corresponding results in refrence and so on. 讨论了置换空间PBPS的强凸性、非常凸性、近强凸性、...
F.-C. Mitroi-Symeonidis and N. Minculete, "On the Jensen functional and strong convexity," Bulletin of the Malaysian Mathematical Sciences Society, vol. 41, no. 1, pp. 311-319, 2018.F.-C. Mitroi-Symeonidis, N. Minculete, On the Jensen functional and the strong convexity, Bull. ...
1、引入正则化损失后，优化目标由经验风险最小化变成了结构风险最小化，要求的最优解从“使得经验风险...