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Streaming and Dynamic Algorithms for Minimum Enclosing Balls in High Dimensions

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6844))

Abstract

At SODA’10, Agarwal and Sharathkumar presented a streaming algorithm for approximating the minimum enclosing ball of a set of points in d-dimensional Euclidean space. Their algorithm requires one pass, uses O(d) space, and was shown to have approximation factor at most \((1+\sqrt{3})/2 +\varepsilon \approx 1.3661\). We prove that the same algorithm has approximation factor less than 1.22, which brings us much closer to a \((1+\sqrt{2})/2 \approx 1.207\) lower bound given by Agarwal and Sharathkumar.

We also apply this technique to the dynamic version of the minimum enclosing ball problem (in the non-streaming setting). We give an O(dn)-space data structure that can maintain a 1.22-approximate minimum enclosing ball in O(d logn) expected amortized time per insertion/deletion.

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References

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Chan, T.M., Pathak, V. (2011). Streaming and Dynamic Algorithms for Minimum Enclosing Balls in High Dimensions. In: Dehne, F., Iacono, J., Sack, JR. (eds) Algorithms and Data Structures. WADS 2011. Lecture Notes in Computer Science, vol 6844. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22300-6_17

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  • DOI: https://doi.org/10.1007/978-3-642-22300-6_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22299-3

  • Online ISBN: 978-3-642-22300-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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