English

Computing Densest $k$-Subgraph with Structural Parameters

Data Structures and Algorithms 2022-07-21 v1

Abstract

\textsc{Densest kk-Subgraph} is the problem to find a vertex subset SS of size kk such that the number of edges in the subgraph induced by SS is maximized. In this paper, we show that \textsc{Densest kk-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 22-approximation 2\tc(G)/2nO(1)2^{\tc(G)/2}n^{O(1)}-time algorithm where \tc(G)\tc(G) is the twin cover number of an input graph GG.

Keywords

Cite

@article{arxiv.2207.09803,
  title  = {Computing Densest $k$-Subgraph with Structural Parameters},
  author = {Tesshu Hanaka},
  journal= {arXiv preprint arXiv:2207.09803},
  year   = {2022}
}
R2 v1 2026-06-25T01:04:39.682Z