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This package provides an efficient implementation of locality-sensitve hashing (LSH)

branch: master
README
This package provides code to implement locality-sensitive hashing (LSH) 
in an optimum fashion.

There are two pieces.  A Python library that implements LSH and a Matlab
routine that calculates the optimum parameters for LSH.

The LSH implementation is based on a tutorial published by IEEE
	Malcolm Slaney, Michael Casey, "Locality-Sensitive Hashing 
	for Finding Nearest Neighbors [Lecture Notes]," 
	Signal Processing Magazine, IEEE , vol.25, no.2, 
	pp.128-131, March 2008
	doi: 10.1109/MSP.2007.914237
	URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4472264&isnumber=4472102
and also available at this URL
	http://www.slaney.org/malcolm/yahoo/Slaney2008-LSHTutorial.pdf

The optimization algorithm is based on this article, which is currently
under review.  Send email to malcolm@ieee.org for a preprint
	Malcolm Slaney, Yury Lifshits, Junfeng He, "Optimal
	Locality-Sensitive Hashing," Submitted to Proceedings of the 
	IEEE, Special Issue on Web-Scale Multimedia, Summer 2012.

Send bug reports and/or comments to 
	malcolm@ieee.org

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