License: Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ITCS.2017.53
URN: urn:nbn:de:0030-drops-81936
URL: https://drops.dagstuhl.de/opus/volltexte/2017/8193/
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Kennedy, Christopher ; Ward, Rachel

Fast Cross-Polytope Locality-Sensitive Hashing

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LIPIcs-ITCS-2017-53.pdf (0.6 MB)


Abstract

We provide a variant of cross-polytope locality sensitive hashing with respect to angular distance which is provably optimal in asymptotic sensitivity and enjoys \mathcal{O}(d \ln d ) hash computation time. Building on a recent result in (Andoni, Indyk, Laarhoven, Razenshteyn '15), we show that optimal asymptotic sensitivity for cross-polytope LSH is retained even when the dense Gaussian matrix is replaced by a fast Johnson-Lindenstrauss transform followed by discrete pseudo-rotation, reducing the hash computation time from \mathcal{O}(d^2) to \mathcal{O}(d \ln d ). Moreover, our scheme achieves the optimal rate of convergence for sensitivity. By incorporating a low-randomness Johnson-Lindenstrauss transform, our scheme can be modified to require only \mathcal{O}(\ln^9(d)) random bits.

BibTeX - Entry

@InProceedings{kennedy_et_al:LIPIcs:2017:8193,
  author =	{Christopher Kennedy and Rachel Ward},
  title =	{{Fast Cross-Polytope Locality-Sensitive Hashing}},
  booktitle =	{8th Innovations in Theoretical Computer Science Conference (ITCS 2017)},
  pages =	{53:1--53:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-029-3},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{67},
  editor =	{Christos H. Papadimitriou},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2017/8193},
  URN =		{urn:nbn:de:0030-drops-81936},
  doi =		{10.4230/LIPIcs.ITCS.2017.53},
  annote =	{Keywords: Locality-sensitive hashing, Dimension reduction, Johnson-Lindenstrauss lemma}
}

Keywords: Locality-sensitive hashing, Dimension reduction, Johnson-Lindenstrauss lemma
Collection: 8th Innovations in Theoretical Computer Science Conference (ITCS 2017)
Issue Date: 2017
Date of publication: 28.11.2017


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