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Exact and Approximation Algorithms for Densest k-Subgraph

机译:密度k子图的精确和近似算法

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The DENSEST k-SUBGRAPH problem is a generalization of the maximum clique problem, in which we are given a graph G and a positive integer k, and we search among the subsets of k vertices of G one inducing a maximum number of edges. In this paper, we present algorithms for finding exact solutions of DENSEST k-SUBGRAPH improving the trivial exponential time complexity of O~* (2~n) and using polynomial space. Two FPT algorithms are also proposed; the first considers as parameter the treewidth of the input graph and uses exponential space, while the second is parameterized by the size of the minimum vertex cover and uses polynomial space. Finally, we propose several approximation algorithms running in moderately exponential or parameterized time.
机译:典型的k子图问题是最大Clique问题的概括,其中我们被赋予图G和正整数k,并且我们搜索G一个诱导最大边缘数量的K顶点的子集之间。在本文中,我们提供了用于查找密度K-Subagraph的精确解的算法,提高O〜*(2〜n)的普通指数时间复杂度并使用多项式空间。还提出了两个FPT算法;第一个认为作为参数输入图的树宽,并使用指数空间,而第二个是由最小顶点盖的大小参数化,并使用多项式空间。最后,我们提出了几种在中等指数或参数化时间中运行的近似算法。

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