文章基本信息

标题：New bounds for soft margin estimator via concavity of Gaussian weighting function
本地全文：下载
作者：Hidayat Ullah ; Muhammad Adil Khan ; Josip Pečarić 等
期刊名称：Advances in Difference Equations
印刷版ISSN：1687-1839
电子版ISSN：1687-1847
出版年度：2020
卷号：2020
期号：1
页码：1-10
DOI：10.1186/s13662-020-03103-z
出版社：Hindawi Publishing Corporation
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.
关键词：Concave function ; Soft margin estimator ; Gaussian weighting function ; Jensen’s inequality ; Jaccard similarity function