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One way to find closest pairs in large datasets is to use hash functions. Inrecent years locality-sensitive hash functions for various metrics have beengiven: projecting an n-cube onto k bits is simple hash function that performswell. In this paper we investigate alternatives to projection. For variousparameters hash functions given by complete decoding algorithms for codes workbetter, and asymptotically random codes perform better than projection.

Optimal hash functions for approximate closest pairs on the n-cube