6 citations · 12 across the 9 of their papers we have counts for
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cs.DS2017
Fast Locality-Sensitive Hashing Frameworks for Approximate Near Neighbor Search
Tobias Christiani
The Indyk-Motwani Locality-Sensitive Hashing (LSH) framework (STOC 1998) is a general technique for constructing a data structure to answer approximate near neighbor queries by usi…
cs.DB2017
Scalable and robust set similarity join
Tobias Christiani, Rasmus Pagh, Johan Sivertsen
Set similarity join is a fundamental and well-studied database operator. It is usually studied in the exact setting where the goal is to compute all pairs of sets that exceed a giv…
cs.DS2017
Distance-Sensitive hashing
Martin Aumüller, Tobias Christiani, Rasmus Pagh +1
Locality-sensitive hashing (LSH) is an important tool for managing high-dimensional noisy or uncertain data, for example in connection with data cleaning (similarity join) and nois…