Identifying reducible k-tuples of vectors with subspace-proximity sensitive hashing/filtering

We introduce and analyse a family of hash and predicate functions that are more likely to produce collisions for small reducible configurations of vectors. These may offer practical improvements to lattice sieving for short vectors. In particular, in one asymptotic regime the family exhibits significantly different convergent behaviour than existing hash functions and predicates.Comment: 20 pages, 5 figure

Book of Abstracts: 2019 Health Equity Summer Research Summit Organized by the Center of Excellence in Health Equity, Training and Research, Baylor College of Medicine, Houston, Texas 77030, USA on June 18th, 2019

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