Variable Bit Quantisation For LSH | Awesome Learning to Hash Add your paper to Learning2Hash

Variable Bit Quantisation For LSH

S. Moran, Lavrenko, Osborne . No Venue 2025 – 21 citations

[Paper]   Search on Google Scholar   Search on Semantic Scholar
Datasets Locality-Sensitive-Hashing Quantization

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 datadriven 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.

Similar Work