Ramsey partitions and proximity data structures

Manor Mendel, Assaf Naor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses the non-linear isomorphic Dvoretzky theorem and the design of good approximate distance oracles for large distortion. We introduce and construct optimal Ramsey partitions, and use them to show that for every ε ∈ (0,1), any n-point metric space has a subset of size n 1-ε which embeds into Hilbert space with distortion 0(1/ε). This result is best possible and improves part of the metric Ramsey theorem of Bartal, Linial, Mendel and Naor [5], in addition to considerably simplifying its proof. We use our new Ramsey partitions to design approximate distance oracles with a universal constant query time, closing a gap left open by Thorup and Zwick in [26]. Namely, we show that for any n point metric space X, and k > 1, there exists an O (k)-approximate distance oracle whose storage requirement is O(n 1+1/k), and whose query time is a universal constant. We also discuss applications to various other geometric data structures, and the relation to well separated pair decompositions.

Original languageEnglish (US)
Title of host publication47th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2006
Pages109-118
Number of pages10
DOIs
Publication statusPublished - 2006
Event47th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2006 - Berkeley, CA, United States
Duration: Oct 21 2006Oct 24 2006

Other

Other47th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2006
CountryUnited States
CityBerkeley, CA
Period10/21/0610/24/06

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Mendel, M., & Naor, A. (2006). Ramsey partitions and proximity data structures. In 47th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2006 (pp. 109-118). [4031348] https://doi.org/10.1109/FOCS.2006.65