New bounds for soft margin estimator via concavity of Gaussian weighting function

被引：15

作者：

Ullah, Hidayat ^{[1
]}

Adil Khan, Muhammad ^{[1
]}

Pecaric, Josip ^{[2
]}

机构：

[1] Univ Peshawar, Dept Math, Peshawar 25000, Pakistan

[2] 2 RUDN Univ, Miklukho Maklaya Str 6, Moscow 117198, Russia

来源：

ADVANCES IN DIFFERENCE EQUATIONS | 2020年 / 2020卷 / 01期

关键词：

Concave function; Soft margin estimator; Gaussian weighting function; Jensen’ s inequality; Jaccard similarity function;

D O I：

10.1186/s13662-020-03103-z

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In the present article, we elaborate on the notion to obtain bounds for the soft margin estimator of "Identification of Patient Zero in Static and Temporal Network-Robustness and Limitations". To achieve these bounds for the soft margin estimator, we utilize the concavity of the Gaussian weighting function and well-known Jensen's inequality. To acquire some more general bounds for the soft margin estimator, we consider some general functions defined on rectangles. We also use the behavior of the Jaccard similarity function to extract some handsome bounds for the soft margin estimator.

引用

页数：10

共 28 条

[1] New estimates for generalized Shannon and Zipf-Mandelbrot entropies via convexity results [J].