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arXiv 2402.07058math.PR
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相关二项过程

Correlated Binomial Process

Moïse Blanchard, Doron Cohen, Aryeh Kontorovich

AI总结:

本文研究相关二项经验过程,发现协方差无法刻画其收敛性,并首次给出基于覆盖数的非平凡上下界。

摘要:

Cohen 和 Kontorovich(COLT 2023)开创了对我们此处所称的二项经验过程的研究:一系列非齐次、归一化且中心化的二项式随机变量的最大绝对值。他们几乎完全分析了二项式相互独立的情形,剩余的空缺由 Blanchard 和 Voráček(ALT 2024)填补。在本工作中,我们研究更为一般且具有挑战性的相关情形。与高斯过程(其行为由协方差结构刻画)形成对比,我们发现,至少有些令人惊讶的是,对于二项过程,协方差甚至不能刻画收敛性。尽管完整的刻画仍然遥不可及,我们迈出了第一步,给出了基于覆盖数的非平凡上下界。

英文摘要:

Cohen and Kontorovich (COLT 2023) initiated the study of what we call here the Binomial Empirical Process: the maximal absolute value of a sequence of inhomogeneous normalized and centered binomials. They almost fully analyzed the case where the binomials are independent, and the remaining gap was closed by Blanchard and Voráček (ALT 2024). In this work, we study the much more general and challenging case with correlations. In contradistinction to Gaussian processes, whose behavior is characterized by the covariance structure, we discover that, at least somewhat surprisingly, for binomial processes covariance does not even characterize convergence. Although a full characterization remains out of reach, we take the first steps with nontrivial upper and lower bounds in terms of covering numbers.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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