Random projection trees for vector quantization

  • Authors:
  • Sanjoy Dasgupta;Yoav Freund

  • Affiliations:
  • Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA;Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA

  • Venue:
  • IEEE Transactions on Information Theory
  • Year:
  • 2009

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Abstract

A simple and computationally efficient scheme for tree-structured vector quantization is presented. Unlike previous methods, its quantization error depends only on the intrinsic dimension of the data distribution, rather than the apparent dimension of the space in which the data happen to lie.