AdaNDV: Adaptive Number of Distinct Value Estimation via Learning to Select and Fuse Estimators
Summary: AdaNDV learns to adaptively select complementary NDV estimators by classifying over- vs under-estimators and picking from each category for error correction. It then predicts fusion weights to combine selected estimators, improving accuracy at large scale versus direct NDV learners. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Xianghong Xu
- 2. Tieying Zhang
- 3. Xiao He
- 4. Haoyang Li
- 5. Rong Kang
- 6. Shuai Wang
- 7. Linhui Xu
- 8. Zhimin Liang
- 9. Shangyu Luo
- 10. Lei Zhang
- 11. Jianjun Chen
Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,936 | VIDEX: A Disaggregated and Extensible Virtual Index for the Cloud and AI Era | 2025 | VLDB | 4.2482599e-05 |
| 10,498 | PLM4NDV: Minimizing Data Access for Number of Distinct Values Estimation with Pre-trained Language Models | 2025 | SIGMOD | 4.1945683e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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