随机图的异常旋转:一个VC理论

L. Addario-Berry, S. Bhamidi, Sébastien Bubeck, L. Devroye, G. Lugosi, R. Oliveira
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引用次数: 2

摘要

本文探讨了大型随机结构对其典型行为的最大偏差。我们引入了一个高维随机图过程的模型,并提出了与Vapnik和Chervonenkis关于平均偏差的类似问题:这个过程要有多“丰富”才能看到非典型行为。特别地,我们研究了在$\mathbb{R}^d$中单位向量索引的Erd\H{o} -R\ enyi随机图的一个自然过程。我们研究了关于三个基本性质的过程偏差:团数,色数和连通性。在所有情况下,我们建立了最小维d的上界和下界,保证了“例外方向”的存在,其中随机图在该性质方面表现出非典型。对于这三个性质中的每一个,建立了四个定理,以描述亚临界和超临界状态下阈值维的上界和下界。
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Exceptional rotations of random graphs: a VC theory
In this paper we explore maximal deviations of large random structures from their typical behavior. We introduce a model for a high-dimensional random graph process and ask analogous questions to those of Vapnik and Chervonenkis for deviations of averages: how "rich" does the process have to be so that one sees atypical behavior. In particular, we study a natural process of Erd\H{o}s-R\'enyi random graphs indexed by unit vectors in $\mathbb{R}^d$. We investigate the deviations of the process with respect to three fundamental properties: clique number, chromatic number, and connectivity. In all cases we establish upper and lower bounds for the minimal dimension $d$ that guarantees the existence of "exceptional directions" in which the random graph behaves atypically with respect to the property. For each of the three properties, four theorems are established, to describe upper and lower bounds for the threshold dimension in the subcritical and supercritical regimes.
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