Year: 2008
Type: preprint
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.
Source: arXiv (Cornell University)
Authors: Dasgupta, Sanjoy, Freund, Yoav
Institution: University of California San Diego
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W2952138658