Abstract
We introduce a scheme for optimally allocating a variable number of bits per LSH hyperplane. Previous approaches assign a constant number of bits per hyperplane. This neglects the fact that a subset of hyperplanes may be more informative than others. Our method, dubbed Variable Bit Quantisation (VBQ), provides a data-driven non-uniform bit allocation across hyperplanes. Despite only using a fraction of the available hyperplanes, VBQ outperforms uniform quantisation by up to 168% for retrieval across standard text and image datasets.
Original language | English |
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Title of host publication | Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) |
Place of Publication | Sofia, Bulgaria |
Publisher | Association for Computational Linguistics |
Pages | 753-758 |
Number of pages | 6 |
ISBN (Print) | 978-1-937284-51-0 |
Publication status | Published - 1 Aug 2013 |