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Kernelization Using Structural Parameters on Sparse Graph Classes

机译:在稀疏图类上使用结构参数的内容

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Meta-theorems for polynomial (linear) kernels have been the subject of intensive research in parameterized complexity. Heretofore, there were meta-theorems for linear kernels on graphs of bounded genus, H-minor-free graphs, and H-topological-minor-free graphs. To the best of our knowledge, there are no known meta-theorems for kernels for any of the larger sparse graph classes: graphs of bounded expansion, locally bounded expansion, and nowhere dense graphs. In this paper we prove meta-theorems for these three graph classes. More specifically, we show that graph problems that have finite integer index (FII) admit linear kernels on hereditary graphs of bounded expansion when parameterized by the size of a modulator to constant-treedepth graphs. For hereditary graph classes of locally bounded expansion, our result yields a quadratic kernel and for hereditary nowhere dense graphs, a polynomial kernel. While our parameter may seem rather strong, a linear kernel result on graphs of bounded expansion with a weaker parameter would for some problems violate known lower bounds. Moreover, we use a relaxed notion of FII which allows us to prove linear kernels for problems such as Longest Path/Cycle and Exact s, t-Path which do not have FII in general graphs.
机译:元定理多项式(线性)的内核已经在参数复杂性深入研究的主题。迄今为止,有元定理上界属,H-次要 - 自由曲线图的曲线图线性内核,和H-拓扑小调 - 自由曲线图。据我们所知,任何较大的稀疏图表类别没有已知的核心定理:有界扩展,局部有界扩展的图形,无处可密集的图形。在本文中,我们证明了元定理这三个图类。更具体地说,我们表明,当由调制器以恒定TREEDEPTH图的尺寸参数具有有限整数指数(FII)图问题承认有界膨胀遗传曲线线性内核。对于局部有界扩张的遗传图类,我们的结果产生的二次核和遗传疏朗图,多项式内核。虽然我们的参数似乎相当强劲,与较弱的参数界扩张的曲线线性核结果将一些问题也就侵犯知下限。此外,我们使用FII的宽松概念,使我们能够证明线性内核的诸如最长路径/周期精确s,这不具备一般图FII T-路径问题。

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