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Fast Approximation Algorithms for Cut-Based Problems in Undirected Graphs

机译:快速近似算法,无向图中的切割问题

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We present a general method of designing fast approximation algorithms for cut-based minimization problems in undirected graphs. In particular, we develop a technique that given any such problem that can be approximated quickly on trees, allows approximating it almost as quickly on general graphs while only losing a poly-logarithmic factor in the approximation guarantee. To illustrate the applicability of our paradigm, we focus our attention on the undirected sparsest cut problem with general demands and the balanced separator problem. By a simple use of our framework, we obtain poly-logarithmic approximation algorithms for these problems that run in time close to linear. The main tool behind our result is an efficient procedure that decomposes general graphs into simpler ones while approximately preserving the cut-flow structure. This decomposition is inspired by the cut-based graph decomposition of R"acke that was developed in the context of oblivious routing schemes, as well as, by the construction of the ultrasparsifiers due to Spiel man and Teng that was employed to preconditioning symmetric diagonally-dominant matrices.
机译:我们介绍了一种设计快速近似算法,以实现基于切割的基于曲线的最小化问题。特别是,我们开发一种技术,给出了可以在树上快速近似的任何此类问题的技术,允许几乎快速地逼近一般图表,同时仅在近似保证中丢失​​多对数因子。为了说明我们的范式的适用性,我们将注意力集中在一般要求和平衡分离器问题中的无向稀疏性问题。通过简单地使用我们的框架,我们获得多对数近似算法,了解这些问题,这些问题在接近线性时运行。我们结果背后的主要工具是一个有效的过程,它们将一般图分解成更简单的过程,同时大致保持切割结构。这种分解是由在不知情的路线方案的上下文中开发的基于切割的图形分解,以及由于Spiel Man和Teng的ultrasparsifiers的构建,该曲线在斯基尔人和腾腾的情况下,用于预处理对象 - 主导矩阵。

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