Nearest-neighbor-preserving embeddings

Piotr Indyk, Assaf Naor

Research output: Contribution to journalArticle

Abstract

In this article we introduce the notion of nearest-neighbor-preserving embeddings. These are randomized embeddings between two metric spaces which preserve the (approximate) nearest-neighbors. We give two examples of such embeddings for Euclidean metrics with low intrinsic dimension. Combining the embeddings with known data structures yields the best-known approximate nearest-neighbor data structures for such metrics.

Original languageEnglish (US)
Article number1273347
JournalACM Transactions on Algorithms
Volume3
Issue number3
DOIs
StatePublished - Aug 1 2007

Fingerprint

Nearest Neighbor
Data Structures
Metric
Metric space
Euclidean

Keywords

  • Dimensionality reduction
  • Doubling spaces
  • Embeddings
  • Nearest neighbor

ASJC Scopus subject areas

  • Mathematics (miscellaneous)

Cite this

Nearest-neighbor-preserving embeddings. / Indyk, Piotr; Naor, Assaf.

In: ACM Transactions on Algorithms, Vol. 3, No. 3, 1273347, 01.08.2007.

Research output: Contribution to journalArticle

Indyk, Piotr ; Naor, Assaf. / Nearest-neighbor-preserving embeddings. In: ACM Transactions on Algorithms. 2007 ; Vol. 3, No. 3.
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