Approximate Nearest Neighbor Search for Low Dimensional Queries
Computational Geometry
2012-09-19 v3 Data Structures and Algorithms
Abstract
We study the Approximate Nearest Neighbor problem for metric spaces where the query points are constrained to lie on a subspace of low doubling dimension, while the data is high-dimensional. We show that this problem can be solved efficiently despite the high dimensionality of the data.
Cite
@article{arxiv.1007.3296,
title = {Approximate Nearest Neighbor Search for Low Dimensional Queries},
author = {Sariel Har-Peled and Nirman Kumar},
journal= {arXiv preprint arXiv:1007.3296},
year = {2012}
}
Comments
25 pages