
arXiv: 1511.08841
Let $G$ be a graph on $n$ vertices and $\mathrm{STAB}_k(G)$ be the convex hull of characteristic vectors of its independent sets of size at most $k$. We study extension complexity of $\mathrm{STAB}_k(G)$ with respect to a fixed parameter $k$ (analogously to, e.g., parameterized computational complexity of problems). We show that for graphs $G$ from a class of bounded expansion it holds that $\mathrm{xc}(\mathrm{STAB}_k(G))\leqslant \mathcal{O}(f(k)\cdot n)$ where the function $f$ depends only on the class. This result can be extended in a simple way to a wide range of similarly defined graph polytopes. In case of general graphs we show that there is {\em no function $f$} such that, for all values of the parameter $k$ and for all graphs on $n$ vertices, the extension complexity of $\mathrm{STAB}_k(G)$ is at most $f(k)\cdot n^{\mathcal{O}(1)}.$ While such results are not surprising since it is known that optimizing over $\mathrm{STAB}_k(G)$ is $FPT$ for graphs of bounded expansion and $W[1]$-hard in general, they are also not trivial and in both cases stronger than the corresponding computational complexity results.
20 pages
FOS: Computer and information sciences, G.1.6, G.1.6; G.2.2; F.1.3, G.2.2, extension complexity, Computational Complexity (cs.CC), fixed-parameter polynomial extension, bounded expansion, Computer Science - Computational Complexity, Vertex subsets with special properties (dominating sets, independent sets, cliques, etc.), independent set polytope, F.1.3
FOS: Computer and information sciences, G.1.6, G.1.6; G.2.2; F.1.3, G.2.2, extension complexity, Computational Complexity (cs.CC), fixed-parameter polynomial extension, bounded expansion, Computer Science - Computational Complexity, Vertex subsets with special properties (dominating sets, independent sets, cliques, etc.), independent set polytope, F.1.3
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
