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Towards a Better Approximation for Sparsest Cut?

机译:寻求更好的近似稀疏切割?

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We give a new (1+ε)-approximation for sparsest cut problem on graphs where small sets expand significantly more than the sparsest cut (expansion of sets of size n/r exceeds that of the sparsest cut by a factor □log nlog r, for some small r; this condition holds for many natural graph families). We give two different algorithms. One involves Guruswami-Sinop rounding on the level-r Lasserre relaxation. The other is combinatorial and involves a new notion called Small Set Expander Flows (inspired by the expander flows of [ARV'09] which we show exists in the input graph. Both algorithms run in time 2O(r) poly(n). We also show similar approximation algorithms in graphs with genus g with an analogous local expansion condition. This is the first algorithm we know of that achieves (1+ε)-approximation on such general family of graphs.
机译:我们给图上最稀疏的切割问题提供了一个新的(1 +&epsi)逼近,其中小集合的扩展远大于最稀疏的切割(大小为n / r的集合的扩展超出最稀疏的裁减的系数为□log nlog r ,对于一些小r;此条件适用于许多自然图族)。我们给出两种不同的算法。其中之一涉及R级Lasserre放松的Guruswami-Sinop取整。另一个是组合的,涉及一个称为小集扩展器流的新概念(受[ARV'09]的扩展器流启发,我们在输入图中显示了这两种算法),两种算法都在时间2O(r)poly(n)上运行。在具有类g的图具有相似的局部展开条件的图中,它也显示了类似的近似算法,这是我们所知的第一个在此类通用图族上实现(1 + eps)逼近的算法。

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