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New tools for graph coloring

Publication ,  Journal Article
Arora, S; Ge, R
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
September 8, 2011

How to color 3 colorable graphs with few colors is a problem of longstanding interest. The best polynomial-time algorithm uses n 0.2072 colors. There are no indications that coloring using say O(log n) colors is hard. It has been suggested that SDP hierarchies could be used to design algorithms that use nε colors for arbitrarily small ε > 0. We explore this possibility in this paper and find some cause for optimism. While the case of general graphs is till open, we can analyse the Lasserre relaxation for two interesting families of graphs. For graphs with low threshold rank (a class of graphs identified in the recent paper of Arora, Barak and Steurer on the unique games problem), Lasserre relaxations can be used to find an independent set of size Ω(n) (i.e., progress towards a coloring with O(log n) colors) in nO(D) time, where D is the threshold rank of the graph. This algorithm is inspired by recent work of Barak, Raghavendra, and Steurer on using Lasserre Hierarchy for unique games. The algorithm can also be used to show that known integrality gap instances for SDP relaxations like strict vector chromatic number cannot survive a few rounds of Lasserre lifting, which also seems reason for optimism. For distance transitive graphs of diameter Δ, we can show how to color them using O(log n) colors in n 2O(Δ) time. This family is interesting because the family of graphs of diameter O(1/ε) is easily seen to be complete for coloring with nε colors. The distance-transitive property implies that the graph "looks" the same in all neighborhoods. The full version of this paper can be found at: http://www.cs.princeton.edu/~rongge/LasserreColoring.pdf. © 2011 Springer-Verlag.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

September 8, 2011

Volume

6845 LNCS

Start / End Page

1 / 12

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Arora, S., & Ge, R. (2011). New tools for graph coloring. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6845 LNCS, 1–12. https://doi.org/10.1007/978-3-642-22935-0_1
Arora, S., and R. Ge. “New tools for graph coloring.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6845 LNCS (September 8, 2011): 1–12. https://doi.org/10.1007/978-3-642-22935-0_1.
Arora S, Ge R. New tools for graph coloring. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2011 Sep 8;6845 LNCS:1–12.
Arora, S., and R. Ge. “New tools for graph coloring.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6845 LNCS, Sept. 2011, pp. 1–12. Scopus, doi:10.1007/978-3-642-22935-0_1.
Arora S, Ge R. New tools for graph coloring. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2011 Sep 8;6845 LNCS:1–12.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

September 8, 2011

Volume

6845 LNCS

Start / End Page

1 / 12

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences