The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data (2000)
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Andrew W. Moore
| Venue: | In Twelfth Conference on Uncertainty in Artificial Intelligence |
| Citations: | 65 - 9 self |
BibTeX
@INPROCEEDINGS{Moore00theanchors,
author = {Andrew W. Moore},
title = {The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data},
booktitle = {In Twelfth Conference on Uncertainty in Artificial Intelligence},
year = {2000},
pages = {397--405},
publisher = {AAAI Press}
}
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Abstract
This paper is about metric data structures in high-dimensional or non-Euclidean space that permit cached sufficient statistics accelerations of learning algorithms.
