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Finding Hidden Cliques of Size root N/e in Nearly Linear Time

机译:在近似线性时间内找到根根N / e的隐藏团

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Consider an Erdos-Renyi random graph in which each edge is present independently with probability , except for a subset of the vertices that form a clique (a completely connected subgraph). We consider the problem of identifying the clique, given a realization of such a random graph. The algorithm of Dekel et al. (ANALCO. SIAM, pp 67-75, 2011) provably identifies the clique in linear time, provided . Spectral methods can be shown to fail on cliques smaller than . In this paper we describe a nearly linear-time algorithm that succeeds with high probability for vertical bar C-N vertical bar (1 - epsilon) N/root e Delta for any epsilon > 0. This is the first algorithm that provably improves over spectral methods. We further generalize the hidden clique problem to other background graphs (the standard case corresponding to the complete graph on vertices). For large-girth regular graphs of degree (Delta + 1) we prove that so-called local algorithms succeed if vertical bar C-N vertical bar (1 - epsilon) N/root e Delta and fail if vertical bar C-N vertical bar (1 - epsilon) N/root e Delta.
机译:考虑一个Erdos-Renyi随机图,其中每个边缘以概率独立存在,除了形成团的顶点子集(完全连接的子图)外。考虑到这样的随机图的实现,我们考虑识别集团的问题。 Dekel等人的算法。 (ANALCO。SIAM,第67-75页,2011年)可证明地以线性时间识别集团。光谱方法可以证明在小于的集团上失败。在本文中,我们描述了一种近似线性时间的算法,对于任何大于0的epsilon,该算法都非常有可能成功获得竖线C-N竖线(1-ε)N /根e Delta。这是可证明地改进了频谱方法的第一个算法。我们进一步将隐藏集团问题推广到其他背景图(标准情况下对应于顶点上的完整图)。对于度数为(Delta + 1)的大周长正则图,我们证明了,如果垂直条CN垂直条(1-ε)N / root e Delta是所谓的局部算法成功,而如果垂直条CN垂直条(1-epsilon)则所谓的局部算法失败。 )N / root e Delta。

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