Sparsification and subexponential approximation

Edouard Bonnet; Vangelis Th. Paschos

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arXiv · 1402.2843

Sparsification and subexponential approximation

Edouard Bonnet·Vangelis Th. Paschos

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Abstract

Instance sparsification is well-known in the world of exact computation since it is very closely linked to the Exponential Time Hypothesis. In this paper, we extend the concept of sparsification in order to capture subexponential time approximation. We develop a new tool for inapproximability, called approximation preserving sparsification and use it in order to get strong inapproximability results in subexponential time for several fundamental optimization problems as Max Independent Set, Min Dominating Set, Min Feedback Vertex Set, and Min Set Cover.

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Edouard Bonnet, Vangelis Th. Paschos. 2014-02-12. Sparsification and subexponential approximation. https://arxiv.org/abs/1402.2843

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