DET-LSH: A Locality-Sensitive Hashing Scheme with Dynamic Encoding Tree for Approximate Nearest Neighbor Search
Summary: DET-LSH introduces DE-Tree, an encoding-based index that avoids expensive space partitioning to speed up indexing and support Euclidean range queries. It issues range queries across multiple independent DE-Trees to reduce missed NNs, with probabilistic guarantees and up to 6× indexing / 2× query speedups. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Jiuqi Wei (Institute of Computing Technology, Chinese Academy of Sciences; University of Chinese Academy of Sciences)
- 2. Botao Peng (Institute of Computing Technology, Chinese Academy of Sciences)
- 3. Xiaodong Lee (Institute of Computing Technology, Chinese Academy of Sciences)
- 4. Themis Palpanas (Université Paris Cité)
BibTeX Citation
@article{wei_vldb24,
title = {{DET-LSH: A Locality-Sensitive Hashing Scheme with Dynamic Encoding Tree for Approximate Nearest Neighbor Search}},
author = {Wei, Jiuqi and Peng, Botao and Lee, Xiaodong and Palpanas, Themis},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {9},
pages = {2241--2254},
doi = {10.14778/3665844.3665854},
url = {https://doi.org/10.14778/3665844.3665854},
year = {2024}
}
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