Testing hypergraph colorability

Authors:
Artur Czumaj;Christian Sohler
Affiliations:
Department of Computer Science, New Jersey Institute of Technology, GITC Building Room No: 4103, Newark, NJ;Heinz Nixdorf Institute and Faculty of Computer Science, Electrical Engineering and Mathematics, University of Paderborn, D-33102 Paderborn, Germany
Venue:
Theoretical Computer Science - Automata, languages and programming
Year:
2005

Citing 22
Cited 3

Self-testing/correcting with applications to numerical problems

Journal of Computer and System Sciences - Special issue: papers from the 22nd ACM symposium on the theory of computing, May 14–16, 1990
Property testing and its connection to learning and approximation

Journal of the ACM (JACM)
Balanced Allocations

SIAM Journal on Computing
A new algorithm approach to the general Lovász local lemma with applications to scheduling and satisfiability problems (extended abstract)

STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Spot-checkers

Journal of Computer and System Sciences - 30th annual ACM symposium on theory of computing
Coloring nonuniform hypergraphs: a new algorithmic approach to the general Lovász local lemma

Proceedings of the ninth international conference on on Random structures and algorithms
Approximating coloring and maximum independent sets in 3-uniform hypergraphs

SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Testing graphs for colorable properties

SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Testing metric properties

STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Testing of matrix properties

STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Random sampling and approximation of MAX-CSP problems

STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Robust Characterizations of Polynomials withApplications to Program Testing

SIAM Journal on Computing
Testing k-colorability

SIAM Journal on Discrete Mathematics
Testing properties of directed graphs: acyclicity and connectivity

Random Structures & Algorithms
Property testers for dense constraint satisfaction programs on finite domains

Random Structures & Algorithms
Abstract Combinatorial Programs and Efficient Property Testers

FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Coloring Bipartite Hypergraphs

Proceedings of the 5th International IPCO Conference on Integer Programming and Combinatorial Optimization
Coloring 2-colorable hypergraphs with a sublinear number of colors

Nordic Journal of Computing
Improved Bounds and Algorithms for Hypergraph Two-Coloring

FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
Hardness of approximate hypergraph coloring

FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Testing satisfiability

Journal of Algorithms
Approximate checking of polynomials and functional equations

FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science

Property Testing: A Learning Theory Perspective

Foundations and Trends® in Machine Learning
Testing Euclidean spanners

Property testing
Testing Euclidean spanners

Property testing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We study the problem of testing properties of hypergraphs. The goal of property testing is to distinguish between the case whether a given object has a certain property or is "far away" from the property. We prove that the fundamental problem of l-colorability of k-uniform hypergraphs can be tested in time independent of the size of the hypergraph. We present a testing algorithm that examines only (k l/ε)O(k) entries of the adjacency matrix of the input hypergraph, where ε is a distance parameter independent of the size of the hypergraph. The algorithm tests only a constant number of entries in the adjacency matrix provided that l, k, and ε are constants. This result is a generalization of previous results about testing graph colorability.