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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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 (2log2n)-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. |
doi_str_mv | 10.1016/j.ipl.2015.02.002 |
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•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.</description><subject>(max,min) matrix product</subject><subject>Algorithms</subject><subject>Algorithms design and analysis</subject><subject>Approximation</subject><subject>Approximation algorithms</subject><subject>Discrete metric space</subject><subject>Geometry</subject><subject>Hyperbolic space</subject><subject>Matrix</subject><subject>Optimization algorithms</subject><subject>Studies</subject><issn>0020-0190</issn><issn>1872-6119</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNp9kEFLwzAUx4MoOKcfwFvAc2te2iYt4kGGm8LAi55Dmry6lHWpSTbYt7djnj09ePx___f4EXIPLAcG4rHP3bjNOYMqZzxnjF-QGdSSZwKguSSzacMyBg27Jjcx9owxURZyRp4Xfhj3ye2-adogXQU_-APdHEcMrd8649KR-o5qal00ARPSAVNwhsZRG7wlV53eRrz7m3PytXz9XLxl64_V--JlnZmiqVJm6xYKa0qUvLFgBOMdojGFEaABubBFUTegW8lrLbStoWnLllshpa5k15hiTh7OvWPwP3uMSfV-H3bTSQVCchB1VZdTCs4pE3yMATs1BjfocFTA1MmS6tVkSZ0sKcbV5GRins4MTu8fHAYVjcOdQesCmqSsd__Qv6pkb2U</recordid><startdate>20150601</startdate><enddate>20150601</enddate><creator>Fournier, Hervé</creator><creator>Ismail, Anas</creator><creator>Vigneron, Antoine</creator><general>Elsevier B.V</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-3891-6271</orcidid></search><sort><creationdate>20150601</creationdate><title>Computing the Gromov hyperbolicity of a discrete metric space</title><author>Fournier, Hervé ; Ismail, Anas ; Vigneron, Antoine</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c395t-d8b13dc4e729d1c602feecc3c61a1e26d33891ab728a6ad819b4b2d677a57f9c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>(max,min) matrix product</topic><topic>Algorithms</topic><topic>Algorithms design and analysis</topic><topic>Approximation</topic><topic>Approximation algorithms</topic><topic>Discrete metric space</topic><topic>Geometry</topic><topic>Hyperbolic space</topic><topic>Matrix</topic><topic>Optimization algorithms</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fournier, Hervé</creatorcontrib><creatorcontrib>Ismail, Anas</creatorcontrib><creatorcontrib>Vigneron, Antoine</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Information processing letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fournier, Hervé</au><au>Ismail, Anas</au><au>Vigneron, Antoine</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computing the Gromov hyperbolicity of a discrete metric space</atitle><jtitle>Information processing letters</jtitle><date>2015-06-01</date><risdate>2015</risdate><volume>115</volume><issue>6-8</issue><spage>576</spage><epage>579</epage><pages>576-579</pages><issn>0020-0190</issn><eissn>1872-6119</eissn><coden>IFPLAT</coden><abstract>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 (2log2n)-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.
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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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