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Approximating vertex cover in dense hypergraphs

Authors: Cardinal, Jean; Karpinski, Marek; Schmied, Richard; Viehmann, Claus;

Approximating vertex cover in dense hypergraphs

Abstract

We consider the minimum vertex cover problem in hypergraphs in which every hyperedge has size k (also known as minimum hitting set problem, or minimum set cover with element frequency k). Simple algorithms exist that provide k-approximations, and this is believed to be the best possible approximation achievable in polynomial time. We show how to exploit density and regularity properties of the input hypergraph to break this barrier. In particular, we provide a randomized polynomial-time algorithm with approximation factor k/(1 +(k-1)d/(k Delta)), where d and Delta are the average and maximum degree, respectively, and Delta must be Omega(n^{k-1}/log n). The proposed algorithm generalizes the recursive sampling technique of Imamura and Iwama (SODA'05) for vertex cover in dense graphs. As a corollary, we obtain an approximation factor k/(2-1/k) for subdense regular hypergraphs, which is shown to be the best possible under the unique games conjecture.

Keywords

FOS: Computer and information sciences, Dense hypergraphs, \(k\)-partite \(k\)-uniform hypergraphs, Hypergraphs, set cover, Theoretical Computer Science, Vertex cover, Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.), Graph algorithms (graph-theoretic aspects), Informatique mathématique, Computer Science - Data Structures and Algorithms, Discrete Mathematics and Combinatorics, Data Structures and Algorithms (cs.DS), approximation algorithms, dense hypergraphs, Approximation algorithms, approximation hardness, vertex cover, Mathématiques, Computational Theory and Mathematics, Approximation hardness, Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.), k-partite k-uniform hypergraphs, Set cover

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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!
8
Top 10%
Average
Average
Green
hybrid