Linear kernels in linear time, or how to save k Colors in O(n2) Steps

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Abstract

This paper examines a parameterized problem that we refer to as n - k GRAPH COLORING, i.e., the problem of determining whether a graph G with n vertices can be colored using n - k colors. As the main result of this paper, we show that there exists a O(kn2 + k2 + 23.8161k) = O(n2) algorithm for n - k GRAPH COLORING for each fixed k. The core technique behind this new parameterized algorithm is kernalization via maximum (and certain maximal) matchings. The core technical content of this paper is a near linear-time kernelization algorithm for n - k CLIQUE COVERING. The near linear-time kernelization algorithm that we present for n - k CLIQUE COVERING produces a linear size (3k - 3) kernel in O(k(n + m)) steps on graphs with n vertices and m edges. The algorithm takes an instance (G, k) of CLIQUE COVERING that asks whether a graph G can be covered using |V| - k cliques and reduces it to the problem of determining whether a graph G′=(V′,E′) of size ≤ 3k - 3 can be covered using |V′| - k′ cliques. We also present a similar near linear-time algorithm that produces a 3k kernel for VERTEX COVER. This second kernelization algorithm is the crown reduction rule. © Springer-Verlag 2004.

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Chor, B., Fellows, M., & Juedes, D. (2004). Linear kernels in linear time, or how to save k Colors in O(n2) Steps. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3353, 257–269. https://doi.org/10.1007/978-3-540-30559-0_22

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