首页> 外文会议>International Colloquium on Automata, Languages and Programming(ICALP 2007); 20070709-13; Wroclaw(PL) >Quasi-randomness and Algorithmic Regularity for Graphs with General Degree Distributions
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Quasi-randomness and Algorithmic Regularity for Graphs with General Degree Distributions

机译:具有一般度分布图的拟随机性和算法正则性

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We deal with two very related subjects: quasi-randomness and regular partitions. The purpose of the concept of quasi-randomness is to measure how much a given graph "resembles" a random one. Moreover, a regular partition approximates a given graph by a bounded number of quasi-random graphs. Regarding quasi-randomness, we present a new spectral characterization of low discrepancy, which extends to sparse graphs. Concerning regular partitions, we present a novel concept of regularity that takes into account the graph's degree distribution, and show that if G = (V, E) satisfies a certain boundedness condition, then G admits a regular partition. In addition, building on the work of Alon and Naor [4], we provide an algorithm that computes a regular partition of a given (possibly sparse) graph G in polynomial time.
机译:我们处理两个非常相关的主题:准随机性和规则分区。准随机性概念的目的是测量给定图在某种程度上“类似于”随机图。此外,规则分区通过一定数量的拟随机图来逼近给定图。关于准随机性,我们提出了一种新的低差异频谱特征,它扩展到稀疏图。关于规则分区,我们提出了一种新颖的规则性概念,该概念考虑了图形的度分布,并表明如果G =(V,E)满足一定的有界条件,则G允许规则分区。此外,基于Alon和Naor [4]的工作,我们提供了一种算法,可以在多项式时间内计算给定(可能是稀疏的)图G的规则分区。

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