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Point-to-Hyperplane Nearest Neighbor Search Beyond the Unit Hypersphere

Summary: Introduces an asymmetric transformation enabling provable hyperplane hashing for Point-to-Hyperplane NNS beyond the unit hypersphere. NH and FH deliver sublinear queries; FH adds a data-dependent multi-partition boost, with NH favoring speed and 3–100× gains on real data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6131
Venue
SIGMOD
Year
2021
Pagerank
5.4976692e-05
Overall Rank
5,456 | 62.05%
DOI
10.1145/3448016.3457240

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