Dynamic Algorithms for Approximating Interdistances

Sergey Bereg; Michael Segal

Dynamic Algorithms for Approximating Interdistances

Sergey Bereg
, Michael Segal

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper we present efficient dynamic algorithms for approximation of kth, 1 ≤ k ≤ (n 2) distance defined by some pair of points from a given set S of n points in d-dimensional space. Our technique is based on the dynamization of well-separated pair decomposition proposed in [11], computing approximate nearest and farthest neighbors [22, 25] and use of persistent search trees [17].

Original language	English
Pages (from-to)	344-355
Number of pages	12
Journal	Nordic Journal of Computing
Volume	11
Issue number	4
State	Published - Dec 2004

Cite this

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title = "Dynamic Algorithms for Approximating Interdistances",

abstract = "In this paper we present efficient dynamic algorithms for approximation of kth, 1 ≤ k ≤ (n 2) distance defined by some pair of points from a given set S of n points in d-dimensional space. Our technique is based on the dynamization of well-separated pair decomposition proposed in [11], computing approximate nearest and farthest neighbors [22, 25] and use of persistent search trees [17].",

author = "Sergey Bereg and Michael Segal",

year = "2004",

month = dec,

language = "English",

volume = "11",

pages = "344--355",

journal = "Nordic Journal of Computing",

issn = "1236-6064",

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AU - Bereg, Sergey

AU - Segal, Michael

PY - 2004/12

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N2 - In this paper we present efficient dynamic algorithms for approximation of kth, 1 ≤ k ≤ (n 2) distance defined by some pair of points from a given set S of n points in d-dimensional space. Our technique is based on the dynamization of well-separated pair decomposition proposed in [11], computing approximate nearest and farthest neighbors [22, 25] and use of persistent search trees [17].

AB - In this paper we present efficient dynamic algorithms for approximation of kth, 1 ≤ k ≤ (n 2) distance defined by some pair of points from a given set S of n points in d-dimensional space. Our technique is based on the dynamization of well-separated pair decomposition proposed in [11], computing approximate nearest and farthest neighbors [22, 25] and use of persistent search trees [17].

M3 - Article

SN - 1236-6064

VL - 11

SP - 344

EP - 355

JO - Nordic Journal of Computing

JF - Nordic Journal of Computing

IS - 4

ER -

Dynamic Algorithms for Approximating Interdistances

Abstract

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