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A Survey on Learning to Hash
[article]
2017
arXiv
pre-print
Nearest neighbor search is a problem of finding the data points from the database such that the distances from them to the query point are the smallest. Learning to hash is one of the major solutions to this problem and has been widely studied recently. In this paper, we present a comprehensive survey of the learning to hash algorithms, categorize them according to the manners of preserving the similarities into: pairwise similarity preserving, multiwise similarity preserving, implicit
arXiv:1606.00185v2
fatcat:j5mnu7lfmvby5pfkg5pffk2nae