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arXiv · 1007.3296

Approximate Nearest Neighbor Search for Low Dimensional Queries

Sariel Har-Peled·Nirman Kumar
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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.

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Sariel Har-Peled, Nirman Kumar. 2010-07-19. Approximate Nearest Neighbor Search for Low Dimensional Queries. https://arxiv.org/abs/1007.3296

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