Optimal LSH

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Slaney, Malcolm Optimal LSH.

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Summary

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.

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Title:

Optimal LSH

Creators:

Slaney, Malcolm

Subjects:

Q Science > QA Mathematics > QA76 Computer software

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Code Repository:

https://github.com/YahooArchive/Optimal-LSH

Description:

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