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arXiv · 1207.7134

Improved approximation algorithms for low-density instances of the Minimum Entropy Set Cover Problem

Cosmin Bonchis·Gabriel Istrate
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Abstract

We study the approximability of instances of the minimum entropy set cover problem, parameterized by the average frequency of a random element in the covering sets. We analyze an algorithm combining a greedy approach with another one biased towards large sets. The algorithm is controled by the percentage of elements to which we apply the biased approach. The optimal parameter choice has a phase transition around average density $e$ and leads to improved approximation guarantees when average element frequency is less than $e$.

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Cosmin Bonchis, Gabriel Istrate. 2012-07-30. Improved approximation algorithms for low-density instances of the Minimum Entropy Set Cover Problem. https://arxiv.org/abs/1207.7134

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