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Random Projection Trees for Vector Quantization

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2 Author(s)
Dasgupta, S. ; Dept. of Comput. Sci. & Eng., Univ. of California, La Jolla, CA ; Freund, Y.

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.

Published in:

Information Theory, IEEE Transactions on  (Volume:55 ,  Issue: 7 )

Date of Publication:

July 2009

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