A new spectral bound on the clique number of graphs

Authors:
Samuel Rota Bulò;Marcello Pelillo
Affiliations:
Dipartimento di Informatica, University of Venice, Italy;Dipartimento di Informatica, University of Venice, Italy
Venue:
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Year:
2010

Citing 15
Cited 0

Model-based recognition in robot vision

ACM Computing Surveys (CSUR)
Labeled point pattern matching by Delaunay triangulation and maximal cliques

Pattern Recognition
Stereo Correspondence Through Feature Grouping and Maximal Cliques

IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational strategies for object recognition

ACM Computing Surveys (CSUR)
An Analysis of Some Graph Theoretical Cluster Techniques

Journal of the ACM (JACM)
Matching Hierarchical Structures Using Association Graphs

IEEE Transactions on Pattern Analysis and Machine Intelligence
Exact bounds on the order of the maximum clique of a graph

Discrete Applied Mathematics
Clique is hard to approximate within n1-

FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
A New Conceptual Clustering Framework

Machine Learning
Replicator Equations, Maximal Cliques, and Graph Isomorphism

Neural Computation
Dominant Sets and Pairwise Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient unsupervised discovery of word categories using symmetric patterns and high frequency words

ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Laplacian spectral bounds for clique and independence numbers of graphs

Journal of Combinatorial Theory Series B
A versatile computer-controlled assembly system

IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
A bound for non-subgraph isomorphism

GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition

Quantified Score

Hi-index	0.01

Visualization

Abstract

Many computer vision and patter recognition problems are intimately related to the maximum clique problem. Due to the intractability of this problem, besides the development of heuristics, a research direction consists in trying to find good bounds on the clique number of graphs. This paper introduces a new spectral upper bound on the clique number of graphs, which is obtained by exploiting an invariance of a continuous characterization of the clique number of graphs introduced by Motzkin and Straus. Experimental results on random graphs show the superiority of our bounds over the standard literature.