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https://doi.org/10.1109/sfcs.2...
Article . 2003 . Peer-reviewed
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Article . 2004 . Peer-reviewed
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Graphs with tiny vector chromatic numbers and huge chromatic numbers

Authors: Feige, Uriel; Langberg, Michael; Schechtman, Gideon;

Graphs with tiny vector chromatic numbers and huge chromatic numbers

Abstract

Summary: \textit{D. Karger, R. Motwani} and \textit{M. Sudan} [J. ACM 45, 246--265 (1998; Zbl 0904.68116)] introduced the notion of a vector coloring of a graph. In particular, they showed that every \(k\)-colorable graph is also vector \(k\)-colorable, and that for constant \(k\), graphs that are vector \(k\)-colorable can be colored by roughly \(\Delta^{1- 2/k}\) colors. Here \(\Delta\) is the maximum degree in the graph and is assumed to be of the order of \(n^{\delta}\) for some \(0 < \delta < 1\). Their results play a major role in the best approximation algorithms used for coloring and for maximum independent sets. We show that for every positive integer \(k\) there are graphs that are vector \(k\)-colorable but do not have independent sets significantly larger than \(n/\Delta^{1- 2/k}\) (and hence cannot be colored with significantly fewer than \(\Delta^{1- 2/k}\) colors). For \(k = O(\log n/\log\log n)\) we show vector \(k\)-colorable graphs that do not have independent sets of size \((\log n)^{c}\), for some constant \(c\). This shows that the vector chromatic number does not approximate the chromatic number within factors better than \(n/\operatorname{polylog} n\). As part of our proof, we analyze ``property testing'' algorithms that distinguish between graphs that have an independent set of size \(n/k\), and graphs that are ``far'' from having such an independent set. Our bounds on the sample size improve previous bounds of \textit{O. Goldreich, S. Goldwasser} and \textit{D. Ron} [J. ACM 45, 653--750 (1998; Zbl 1065.68575)] for this problem.

Country
United States
Keywords

independent set, Coloring of graphs and hypergraphs, chromatic number, Graph theory (including graph drawing) in computer science, Graph algorithms (graph-theoretic aspects), Semidefinite programming, property testing, semidefinite programming, approximation algorithms, Approximation algorithms, 004

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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Top 10%
Average
Green
bronze