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This technical note compares two coding (quantization) schemes for randomprojections in the context of sub-linear time approximate near neighbor search.The first scheme is based on uniform quantization while the second schemeutilizes a uniform quantization plus a uniformly random offset (which has beenpopular in practice). The prior work compared the two schemes in the context ofsimilarity estimation and training linear classifiers, with the conclusion thatthe step of random offset is not necessary and may hurt the performance(depending on the similarity level). The task of near neighbor search isrelated to similarity estimation with importance distinctions and requires ownstudy. In this paper, we demonstrate that in the context of near neighborsearch, the step of random offset is not needed either and may hurt theperformance (sometimes significantly so, depending on the similarity and otherparameters).

Coding for Random Projections and Approximate Near Neighbor Search