Tight lower bound on the probability of a binomial exceeding Cross Mark its expectation

被引：31

作者：

Greenberg, Spencer ^{[1
]}

Mohri, Mehryar ^{[1
,2
]}

机构：

[1] Courant Inst Math Sci, New York, NY 10012 USA

[2] Google Res, New York, NY 10011 USA

来源：

STATISTICS & PROBABILITY LETTERS | 2014年 / 86卷

关键词：

Binomial distribution; Lower bound; Expected value; Relative deviation; Machine learning;

D O I：

10.1016/j.spl.2013.12.009

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in learning theory and generalization bounds for unbounded loss functions. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：91 / 98

页数：8

共 11 条

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