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APPROX

2006

Springer

2006

Springer

In the minimum entropy set cover problem, one is given a collection of k sets which collectively cover an n-element ground set. A feasible solution of the problem is a partition of the ground set into parts such that each part is included in some of the k given sets. Such a partition defines a probability distribution, obtained by dividing each part size by n. The goal is to find a feasible solution minimizing the (binary) entropy of the corresponding distribution. Halperin and Karp have recently proved that the greedy algorithm always returns a solution whose cost is at most the optimum plus a constant. We improve their result by showing that the greedy algorithm approximates the minimum entropy set cover problem within an additive error of 1 nat

Related Content

Added |
20 Aug 2010 |

Updated |
20 Aug 2010 |

Type |
Conference |

Year |
2006 |

Where |
APPROX |

Authors |
Jean Cardinal, Samuel Fiorini, Gwenaël Joret |

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