On the Parameterized Complexity of Sparsest Cut and Small-set Expansion Problems
Abstract
We present a parameterized dichotomy for the \textsc{-Sparsest Cut} problem in weighted and unweighted versions. In particular, we show that the weighted \textsc{-Sparsest Cut} problem is NP-hard for every even on graphs with bounded vertex cover number. Also, the unweighted \textsc{-Sparsest Cut} problem is W[1]-hard when parameterized by the three combined parameters tree-depth, feedback vertex set number, and . On the positive side, we show that unweighted \textsc{-Sparsest Cut} problem is FPT when parameterized by the vertex cover number and , and when is fixed, it is FPT with respect to the treewidth. Moreover, we show that the generalized version \textsc{-Small-Set Expansion} problem is FPT when parameterized by and the maximum degree of the graph, though it is W[1]-hard for each of these parameters separately.
Cite
@article{arxiv.1910.12353,
title = {On the Parameterized Complexity of Sparsest Cut and Small-set Expansion Problems},
author = {Ramin Javadi and Amir Nikabadi},
journal= {arXiv preprint arXiv:1910.12353},
year = {2023}
}