Sharp finite-sample concentration of independent variables

arXiv (Cornell University)(2020)

引用 0|浏览1
暂无评分
摘要
We show an extension of Sanov's theorem on large deviations, controlling the tail probabilities of i.i.d. random variables with matching concentration and anti-concentration bounds. This result has a general scope, applies to samples of any size, and has a short information-theoretic proof using elementary techniques.
更多
查看译文
关键词
concentration,independent variables,finite-sample
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要