Local Max-Cut on Sparse Graphs

October 31, 2023 Β· Declared Dead Β· πŸ› Embedded Systems and Applications

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Authors Gregory Schwartzman arXiv ID 2311.00182 Category cs.DS: Data Structures & Algorithms Citations 1 Venue Embedded Systems and Applications Last Checked 4 months ago
Abstract
We bound the smoothed running time of the FLIP algorithm for local Max-Cut as a function of $Ξ±$, the arboricity of the input graph. We show that, with high probability and in expectation, the following holds (where $n$ is the number of nodes and $Ο†$ is the smoothing parameter): 1) When $Ξ±= O(\log^{1-Ξ΄} n)$ FLIP terminates in $Ο†poly(n)$ iterations, where $Ξ΄\in (0,1]$ is an arbitrarily small constant. Previous to our results the only graph families for which FLIP was known to achieve a smoothed polynomial running time were complete graphs and graphs with logarithmic maximum degree. 2) For arbitrary values of $Ξ±$ we get a running time of $Ο†n^{O(\fracΞ±{\log n} + \log Ξ±)}$. This improves over the best known running time for general graphs of $Ο†n^{O(\sqrt{ \log n })}$ for $Ξ±= o(\log^{1.5} n)$. Specifically, when $Ξ±= O(\log n)$ we get a significantly faster running time of $Ο†n^{O(\log \log n)}$.
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