Affiliation:
1. Massachusetts Institute of Technology, Cambridge, MA
Abstract
In this article, we give an overview of efficient algorithms for the approximate and exact nearest neighbor problem. The goal is to preprocess a dataset of objects (e.g., images) so that later, given a new query object, one can quickly return the dataset object that is most similar to the query. The problem is of significant interest in a wide variety of areas.
Funder
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Reference37 articles.
1. Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
2. Andoni A. and Indyk P. 2004. E2lsh: Exact Euclidean localitysensitive hashing. http://web.mit.edu/andoni/www/LSH/. Andoni A. and Indyk P. 2004. E2lsh: Exact Euclidean localitysensitive hashing. http://web.mit.edu/andoni/www/LSH/.
3. Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions
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