CoveringLSH: Locality-sensitive Hashing without False Negatives

Rasmus Pagh

Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review


We consider a new construction of locality-sensitive hash functions for Hamming space that is covering in the sense that is it guaranteed to produce a collision for every pair of vectors within a given radius r. The construction is efficient in the sense that the expected number of hash collisions between vectors at distance cr, for a given c>1, comes close to that of the best possible data independent LSH without the covering guarantee, namely, the seminal LSH construction of Indyk and Motwani (STOC’98). The efficiency of the new construction essentially matches their bound when the search radius is not too large—e.g., when cr = o(log (n)/ log log n), where n is the number of points in the dataset, and when cr = log (n)/k, where k is an integer constant. In general, it differs by at most a factor ln (4) in the exponent of the time bounds. As a consequence, LSH-based similarity search in Hamming space can avoid the problem of false negatives at little or no cost in efficiency.
Original languageEnglish
Article number29
JournalA C M Transactions on Algorithms
Issue number3
Publication statusPublished - 2018


  • recall
  • locality-sensitive hashing
  • high-dimensional
  • Similarity search
  • Theory of computation


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