Improved approximations of packing and covering problems
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
A tight analysis of the greedy algorithm for set cover
Journal of Algorithms
Improved performance of the greedy algorithm for partial cover
Information Processing Letters
A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
On the hardness of approximating minimization problems
Journal of the ACM (JACM)
Improved approximation algorithms for the vertex cover problem in graphs and hypergraphs
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Approximation algorithms
Computational Complexity of Machine Learning
Computational Complexity of Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Covering analysis of the greedy algorithm for partial cover
Algorithms and Applications
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Let H be a hypergraph with m edges and maximum degree Δ. Given ε ≥ 0, a (1 - ε)-vertex-cover is a collection T of vertices which hits at least (1 - ε)m edges. We denote min |T| by τε. Note that T = To is the (full) covering number of H.In this paper we study the performance ratio of the greedy cover algorithm for this "partial vertex cover" problem and compare it to random choice and to optimal fractional cover. For the first time, we prove a performance ratio bound depending only on ε 0 for an important class of hypergraphs.Let T* be the optimal fractional covering number (ε = 0). Lovász (1975) showed that To ≤ (1 + In Δ)T*, where Δ is the maximum degree, using the greedy cover algorithm; it follows that the greedy cover algorithm has performance ratio ≤ 1 + In Δ.Kearns (1990) introduced the partial vertex cover problem. He proved that the performance ratio of the greedy cover algorithm for the partial vertex cover problem is ≤ 5+2 In m regardless of ε ≥ 0. Later, Slavík (1997a) improved the bound to 1 + In Δ. Kearns' and Slavík's bounds apply to weighted hypergraphs; in this paper we study the unweighted case only.Our main result is that for ε 0, the performance ratio of the greedy algorithm is ≤ 1 + In(ΔT*/em). As a corollary, we confirm Babai's conjecture that the greedy cover algorithm has a performance ratio ≤ 1+In(1/ε) for regular and uniform hypergraphs. This special case has significant applications. On the other hand we present examples in which the performance ratio reaches In Δ if either one of the conditions of regularity and uniformity is dropped.We also show that the ratio of the greedy (1 - ε)-cover to T* is ≤ 1/ε for all hypergraphs. Note that this bound again does not depend on the parameters of the hypergraph and is the first such bound.We demonstrate the tightness of our bounds by presenting examples of regular and uniform hypergraphs that have performance ratio ≥ In(1/ε) for partial vertex covering. We obtain similar matching upper and lower bounds for the integrality gap of partial covering.We compare the bounds attained by the greedy cover algorithm with random choice. We establish a counterintuitive gap of In(1/ε) in favor of random choice for a class of regular and uniform hypergraphs.