English

Detecting and Characterizing Small Dense Bipartite-like Subgraphs by the Bipartiteness Ratio Measure

Data Structures and Algorithms 2013-09-19 v2

Abstract

We study the problem of finding and characterizing subgraphs with small \textit{bipartiteness ratio}. We give a bicriteria approximation algorithm \verb|SwpDB| such that if there exists a subset SS of volume at most kk and bipartiteness ratio θ\theta, then for any 0<ϵ<1/20<\epsilon<1/2, it finds a set SS' of volume at most 2k1+ϵ2k^{1+\epsilon} and bipartiteness ratio at most 4θ/ϵ4\sqrt{\theta/\epsilon}. By combining a truncation operation, we give a local algorithm \verb|LocDB|, which has asymptotically the same approximation guarantee as the algorithm \verb|SwpDB| on both the volume and bipartiteness ratio of the output set, and runs in time O(ϵ2θ2k1+ϵln3k)O(\epsilon^2\theta^{-2}k^{1+\epsilon}\ln^3k), independent of the size of the graph. Finally, we give a spectral characterization of the small dense bipartite-like subgraphs by using the kkth \textit{largest} eigenvalue of the Laplacian of the graph.

Keywords

Cite

@article{arxiv.1209.5045,
  title  = {Detecting and Characterizing Small Dense Bipartite-like Subgraphs by the Bipartiteness Ratio Measure},
  author = {Angsheng Li and Pan Peng},
  journal= {arXiv preprint arXiv:1209.5045},
  year   = {2013}
}

Comments

17 pages; ISAAC 2013