Computing densest k-subgraph with structural parameters

Tesshu Hanaka ()
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Tesshu Hanaka: Kyushu University

Journal of Combinatorial Optimization, 2023, vol. 45, issue 1, No 1, 17 pages

Abstract: Abstract Densest k-Subgraph is the problem to find a vertex subset S of size k such that the number of edges in the subgraph induced by S is maximized. In this paper, we show that Densest k-Subgraph is fixed parameter tractable when parameterized by neighborhood diversity, block deletion number, distance-hereditary deletion number, and cograph deletion number, respectively. Furthermore, we give a 2-approximation $$2^{{{\texttt{tc}}(G)}/2}n^{O(1)}$$ 2 tc ( G ) / 2 n O ( 1 ) -time algorithm where $${{\texttt{tc}}(G)}$$ tc ( G ) is the twin cover number of an input graph G.

Keywords: Densest subgraphs; Sparsest subgraphs; Fixed parameter tractability; Structural parameters; Approximation algorithm (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10878-022-00927-1

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