In this paper, we propose a new method to decompose a graph into maximal k-edge-connected components, based on random contraction of edges. Our method is simple ...

Sep 19, 2024 · Our method is simple to implement but improves performance drastically. We experimentally show that our method can successfully decompose large ...

Linear-Time Enumeration of Maximal k-Edge-Connected. Subgraphs in Large Networks by Random Contraction. Takuya Akiba. The University of Tokyo. Tokyo, 113-0033 ...

A new method to decompose a graph into maximal k-edge-connected components, based on random contraction of edges is proposed, which is simple to implement ...

In this paper, we propose a new method to decompose a graph into maximal k-edge-connected components, based on random contraction of edges. Our method is simple ...

Linear-Time Enumeration of Maximal k-Edge-Connected. Subgraphs in Large Networks by Random Contraction. Takuya Akiba. The University of Tokyo. Tokyo, 113-0033 ...

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This software library efficiently decomposes a graph into maximal k-edge-connected subgraphs (MkECSs) by our new randomized algorithm based on random ...

Jun 30, 2023 · Abstract. We give the first almost-linear time algorithm for computing the maximal k-edge-connected subgraphs of an undirected unweighted ...

Aug 30, 2023 · We give the first almost-linear time algorithm for computing the maximal k-edge-connected subgraphs of an undirected unweighted graph for any constant k.