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#### New techniques for exact and approximate dynamic closest-point problems

##### MPS-Authors
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Kapoor,  Sanjiv
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

/persons/resource/persons45509

Smid,  Michiel
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

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##### Fulltext (public)

MPI-I-93-159.pdf
(Any fulltext), 174KB

##### Supplementary Material (public)
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##### Citation

Kapoor, S., & Smid, M.(1993). New techniques for exact and approximate dynamic closest-point problems (MPI-I-93-159). Saarbrücken: Max-Planck-Institut für Informatik.

Cite as: http://hdl.handle.net/11858/00-001M-0000-0014-B42E-2
##### Abstract
Let $S$ be a set of $n$ points in $\IR^{D}$. It is shown that a range tree can be used to find an $L_{\infty}$-nearest neighbor in $S$ of any query point, in $O((\log n)^{D-1} \log\log n)$ time. This data structure has size $O(n (\log n)^{D-1})$ and an amortized update time of $O((\log n)^{D-1} \log\log n)$. This result is used to solve the $(1+\epsilon)$-approximate $L_{2}$-nearest neighbor problem within the same bounds. In this problem, for any query point $p$, a point $q \in S$ is computed such that the euclidean distance between $p$ and $q$ is at most $(1+\epsilon)$ times the euclidean distance between $p$ and its true nearest neighbor. This is the first dynamic data structure for this problem having close to linear size and polylogarithmic query and update times.