ONe Index for All Kernels (ONIAK): A Zero Re-Indexing LSH Solution to ANNS-ALT (After Linear Transformation)
Summary: ONe Index for All Kernels (ONIAK) builds a universal index for ANNS-ALT across arbitrary query matrices, enabling zero re-indexing for d ≤ 200. FGoeQF tackles the dimension blowup in indexing; a Johnson-Lindenstrauss transform (JLT)-based ANNS-ALT/ALTD solution scales to large d. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Jingfan Meng
- 2. Huayi Wang
- 3. Jun Xu
- 4. Mitsunori Ogihara
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 400 | Multi-Probe LSH: Efficient Indexing for High-Dimensional Similarity Search | 2007 | VLDB | 0.0002427237 |
| 562 | Query-Aware Locality-Sensitive Hashing for Approximate Nearest Neighbor Search | 2016 | VLDB | 0.00020091752 |
| 867 | SRS: Solving c-Approximate Nearest Neighbor Queries in High Dimensional Euclidean Space with a Tiny Index | 2015 | VLDB | 0.00015792021 |
| 2,181 | PM-LSH: A Fast and Accurate LSH Framework for High-Dimensional Approximate NN Search | 2020 | VLDB | 9.3451821e-05 |
| 2,641 | Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science | 2018 | VLDB | 8.3905374e-05 |
| 5,456 | Point-to-Hyperplane Nearest Neighbor Search Beyond the Unit Hypersphere | 2021 | SIGMOD | 5.4976692e-05 |
| 6,107 | Continuously Adaptive Similarity Search | 2020 | SIGMOD | 5.2066612e-05 |
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