Random Projection Trees for Vector Quantization
Dasgupta, S.
Freund, Y.
Dept. of Comput. Sci. & Eng., Univ. of California, La Jolla, CA;
This paper appears in: Information Theory, IEEE Transactions on
Publication Date: July 2009
Volume: 55,
Issue: 7
On page(s): 3229-3242
ISSN: 0018-9448
INSPEC Accession Number: 10729399
Digital Object Identifier: 10.1109/TIT.2009.2021326
Current Version Published: 2009-06-16
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.
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