Computing the Gromov hyperbolicity of a discrete metric space

We give exact and approximation algorithms for computing the Gromov hyperbolicity of an n-point discrete metric space. We observe that computing the Gromov hyperbolicity from a fixed base-point reduces to a (max,min) matrix product. Hence, using the (max,min) matrix product algorithm by Duan and Pet...

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Veröffentlicht in:Information processing letters 2015-06, Vol.115 (6-8), p.576-579
Hauptverfasser: Fournier, Hervé, Ismail, Anas, Vigneron, Antoine
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description We give exact and approximation algorithms for computing the Gromov hyperbolicity of an n-point discrete metric space. We observe that computing the Gromov hyperbolicity from a fixed base-point reduces to a (max,min) matrix product. Hence, using the (max,min) matrix product algorithm by Duan and Pettie, the fixed base-point hyperbolicity can be determined in O(n2.69) time. It follows that the Gromov hyperbolicity can be computed in O(n3.69) time, and a 2-approximation can be found in O(n2.69) time. We also give a (2log2⁡n)-approximation algorithm that runs in O(n2) time, based on a tree-metric embedding by Gromov. We also show that hyperbolicity at a fixed base-point cannot be computed in O(n2.05) time, unless there exists a faster algorithm for (max,min) matrix multiplication than currently known. •We consider the problem of computing the Gromov hyperbolicity of a metric space.•We present an efficient exact algorithm for this problem.•We also present efficient approximation algorithms.•We give a hardness result.
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subjects (max,min) matrix product
Algorithms
Algorithms design and analysis
Approximation
Approximation algorithms
Discrete metric space
Geometry
Hyperbolic space
Matrix
Optimization algorithms
Studies
title Computing the Gromov hyperbolicity of a discrete metric space
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