Locality-sensitive Filtering
Locality-Sensitive Filtering is a hash-based indexing method that distinguishes itself by enabling approximate nearest neighbor search through the prioritization of candidate points likely to be in proximity to the query, based on shared hash bucket assignments across multiple filtering tables.
23
Publications
1.3K
Citations
75
Authors
50
Institutions
Publications per year
2017–2026
6
Parents
23
Fast, Accurate Detection of 100,000 Object Classes on a Single Machine
Thomas Dean, Mark A. Ruzon, Mark Segal et al. · 2013 · 317 citations
New directions in nearest neighbor searching with applications to lattice sieving
Anja Becker, Léo Ducas, Nicolas Gama et al. · 2015 · 222 citations
Distance-Sensitive Bloom Filters
Adam Kirsch, Michael Mitzenmacher · 2006 · 81 citations
1–5 of 23
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50

City University of Hong Kong
Hong Kong, Hong Kong
2 h-index
4 publications
118 citations

IT University of Copenhagen
Copenhagen, Denmark
2 h-index
2 publications
34 citations
Laboratoire de Mathématiques Blaise Pascal
Aubière, France
1 h-index
1 publications
222 citations
Northeast Electric Power University
Jilin City, China
1 h-index
2 publications
52 citations
Intel (India)
Bengaluru, India
1 h-index
1 publications
16 citations
United States Navy
Washington, United States
1 h-index
1 publications
16 citations
Ngee Ann Polytechnic
Singapore, Singapore
1 h-index
2 publications
184 citations

Harvard University Press
Cambridge, United States
1 h-index
2 publications
162 citations
1–8 of 50
2 publications · 82 citations
2
h-index
Conference · 1 publications · 42 citations
1
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Repository · 1 publications · 23 citations
1
h-index
1 publications · 26 citations
1
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TPDS · 1 publications · 16 citations
1
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1–5