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Near-linear Time Approximation Schemes for Clustering in Doubling Metrics

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10439297" target="_blank" >RIV/00216208:11320/21:10439297 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=r25yeVePgg" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=r25yeVePgg</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3477541" target="_blank" >10.1145/3477541</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Near-linear Time Approximation Schemes for Clustering in Doubling Metrics

  • Original language description

    We consider the classic Facility Location, k-Median, and k-Means problems in metric spaces of doubling dimension d. We give nearly linear-time approximation schemes for each problem. The complexity of our algorithms is (O) over tilde (2((1/epsilon)O(d2) )n), making a significant improvement over the state-of-the-art algorithms that run in time n((d/epsilon)O(d)). Moreover, we show how to extend the techniques used to get the first efficient approximation schemes for the problems of prize-collecting k-Median and k-Means and efficient bicriteria approximation schemes for k-Median with outliers, k-Means with outliers and k-Center.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GX19-27871X" target="_blank" >GX19-27871X: Efficient approximation algorithms and circuit complexity</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of the ACM

  • ISSN

    0004-5411

  • e-ISSN

  • Volume of the periodical

    68

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    34

  • Pages from-to

    44

  • UT code for WoS article

    000744649600005

  • EID of the result in the Scopus database

    2-s2.0-85078407097