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A streaming algorithm for 2-center with outliers in high dimensions

Hatami, B ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1016/j.comgeo.2016.07.002
  3. Abstract:
  4. We study the 2-center problem with outliers in high-dimensional data streams. Given a stream of points in arbitrary d dimensions, the goal is to find two congruent balls of minimum radius covering all but at most z points. We present a (1.8+ε)-approximation streaming algorithm, improving over the previous (4+ε)-approximation algorithm available for the problem. The space complexity and update time of our algorithm are poly(d,z,1/ε), independent of the size of the stream. © 2016 Elsevier B.V
  5. Keywords:
  6. Algorithms ; Clustering algorithms ; Data communication systems ; Data mining ; Statistics ; D dimensions ; Data stream ; High dimensions ; High-dimensional data streams ; K-center ; Outlier ; Space complexity ; Streaming algorithm ; Approximation algorithms
  7. Source: Computational Geometry: Theory and Applications ; Volume 60 , 2017 , Pages 26-36 ; 09257721 (ISSN)
  8. URL: https://www.sciencedirect.com/science/article/pii/S0925772116300645