Communication-Efficient Vector Manipulations on Binary N-Cubes

One way to find closest pairs in large datasets is to use hash functions [6], [12]. In recent years locality-se nsitive hash functions for various metrics have been given: project ing an n-cube ontok bits is simple hash function that performs well. In this paper we investigate alternatives to projection. For various parameters hash functions given by complete decodi ng algorithms for codes work better, and asymptotically random codes perform better than projection.