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JHQ: Johnson-Lindenstrauss Enhanced Hierarchical Quantization for High-Dimensional Approximate Nearest Neighbor Search

Summary: Training-free ANN quantization via orthogonal Johnson-Lindenstrauss transform: near-Gaussian, independent dimensions enable fast codebook construction with provable error bounds. JHQ adds two-level primary/residual quantization for scalable candidate filtering and refinement, yielding large index-build and query speedups on high-d ANN. (summarized by gpt-5.4-mini on May 27 2026)

Paper ID
hcf78fd496e788419
Venue
VLDB
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,730 | 27.86%
DOI
10.14778/3801059.3801067

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Authors

BibTeX Citation

@article{han_vldb26,
        title = {{JHQ: Johnson-Lindenstrauss Enhanced Hierarchical Quantization for High-Dimensional Approximate Nearest Neighbor Search}},
        author = {Han, Jiabao and Zhang, Mengxuan and Trajcevski, Goce},
        journal = {PVLDB},
        series = {{VLDB} '26},
        volume = {19},
        number = {7},
        pages = {1530--1543},
        doi = {10.14778/3801059.3801067},
        url = {https://doi.org/10.14778/3801059.3801067},
        year = {2026}
}

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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
20 Similarity Search in High Dimensions via Hashing 1999 VLDB 0.00057568153
45 A Quantitative Analysis and Performance Study for Similarity-Search Methods in High-Dimensional Spaces 1998 VLDB 0.0004503446
74 Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph 2019 VLDB 0.00037091678
280 Multi-Probe LSH: Efficient Indexing for High-Dimensional Similarity Search 2007 VLDB 0.0002230467
298 Query-Aware Locality-Sensitive Hashing for Approximate Nearest Neighbor Search 2016 VLDB 0.00021833987
338 Locality-Sensitive Hashing Scheme Based on Dynamic Collision Counting 2012 SIGMOD 0.00020585187
562 SRS: Solving c-Approximate Nearest Neighbor Queries in High Dimensional Euclidean Space with a Tiny Index 2015 VLDB 0.00016335405
576 Quality and Efficiency in High Dimensional Nearest Neighbor Search 2009 SIGMOD 0.00016121388
650 HD-Index: Pushing the Scalability-Accuracy Boundary for Approximate kNN Search in High-Dimensional Spaces 2018 VLDB 0.00015149775
804 RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search 2024 SIGMOD 0.00013832333
2,060 Similarity search in the blink of an eye with compressed indices 2023 VLDB 9.0983169e-05
2,448 DeltaPQ: Lossless Product Quantization Code Compression for High Dimensional Similarity Search 2020 VLDB 8.4494625e-05
2,821 Practical and Asymptotically Optimal Quantization of High-Dimensional Vectors in Euclidean Space for Approximate Nearest Neighbor Search 2025 SIGMOD 7.9711961e-05
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