Selectivity Functions of Range Queries are Learnable*
Summary: ML-based selectivity estimation for range queries; bounded VC-dimension implies learnable functions. Empirical results show simple learners match specialized methods on orthogonal, linear, and distance-based ranges with theory-sized training data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Xiao Hu
- 2. Yuxi Liu
- 3. Haibo Xiu
- 4. Pankaj K. Agarwal
- 5. Debmalya Panigrahi
- 6. Sudeepa Roy
- 7. Jun Yang
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,565 | Toward Interpretable and Actionable Data Analysis with Explanations and Causality | 2022 | VLDB | 5.0081626e-05 |
| 8,448 | PARQO: Penalty-Aware Robust Plan Selection in Query Optimization | 2024 | VLDB | 4.5100508e-05 |
| 8,636 | WISK: A Workload-aware Learned Index for Spatial Keyword Queries | 2023 | SIGMOD | 4.4801284e-05 |
| 9,107 | NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks | 2023 | SIGMOD | 4.3950706e-05 |
| 9,485 | Spatial Query Optimization With Learning | 2024 | VLDB | 4.3341665e-05 |
| 9,812 | A Practical Theory of Generalization in Selectivity Learning | 2025 | VLDB | 4.2783272e-05 |
| 10,619 | Data-Agnostic Cardinality Learning from Imperfect Workloads | 2025 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 372 | Selectivity Estimation using Probabilistic Models | 2001 | SIGMOD | 0.00025354779 |
| 9,351 | On Efficient Approximate Queries over Machine Learning Models | 2023 | VLDB | 4.3524472e-05 |
| 5,861 | Machine Learning for Databases | 2021 | VLDB | 5.298883e-05 |
| 5,337 | Learned Index Benefits: Machine Learning Based Index Performance Estimation | 2022 | VLDB | 5.5635208e-05 |
| 9,120 | Deep Query Optimization | 2019 | SIGMOD | 4.392741e-05 |
| 9,812 | A Practical Theory of Generalization in Selectivity Learning | 2025 | VLDB | 4.2783272e-05 |
| 8,384 | Consistent and Flexible Selectivity Estimation for High-Dimensional Data | 2021 | SIGMOD | 4.5304673e-05 |
| 3,954 | Efficiently Approximating Selectivity Functions using Low Overhead Regression Models | 2020 | VLDB | 6.5926838e-05 |
| 2,364 | Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries | 2020 | SIGMOD | 8.9554751e-05 |
| 1,254 | Selectivity Estimation for Range Predicates using Lightweight Models | 2019 | VLDB | 0.00013027411 |