English

Practical Computation of Graph VC-Dimension

Data Structures and Algorithms 2024-05-14 v1

Abstract

For any set system H=(V,R), R2VH=(V,R), \ R \subseteq 2^V, a subset SVS \subseteq V is called \emph{shattered} if every SSS' \subseteq S results from the intersection of SS with some set in R\R. The \emph{VC-dimension} of HH is the size of a largest shattered set in VV. In this paper, we focus on the problem of computing the VC-dimension of graphs. In particular, given a graph G=(V,E)G=(V,E), the VC-dimension of GG is defined as the VC-dimension of (V,N)(V, \mathcal N), where N\mathcal N contains each subset of VV that can be obtained as the closed neighborhood of some vertex vVv \in V in GG. Our main contribution is an algorithm for computing the VC-dimension of any graph, whose effectiveness is shown through experiments on various types of practical graphs, including graphs with millions of vertices. A key aspect of its efficiency resides in the fact that practical graphs have small VC-dimension, up to 8 in our experiments. As a side-product, we present several new bounds relating the graph VC-dimension to other classical graph theoretical notions. We also establish the W[1]W[1]-hardness of the graph VC-dimension problem by extending a previous result for arbitrary set systems.

Keywords

Cite

@article{arxiv.2405.07588,
  title  = {Practical Computation of Graph VC-Dimension},
  author = {David Coudert and Mónika Csikós and Guillaume Ducoffe and Laurent Viennot},
  journal= {arXiv preprint arXiv:2405.07588},
  year   = {2024}
}
R2 v1 2026-06-28T16:25:07.774Z