Learning-based Property Estimation with Polynomials
Summary: Learning-based, polynomial-approximation framework for frequency-based property estimation (NDV, entropy, power sums) from samples/histograms. Learns polynomial coefficients to combine ML adaptability with theoretical error guarantees, unifying previously separate statistical and learning-based estimators. (summarized by gpt-5.4-mini on May 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiajun Li
- 2. Runlin Lei
- 3. Sibo Wang
- 4. Zhewei Wei
- 5. Bolin Ding
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,507 | PLM4NDV: Minimizing Data Access for Number of Distinct Values Estimation with Pre-trained Language Models | 2025 | SIGMOD | 4.1905499e-05 |
| 10,543 | AdaNDV: Adaptive Number of Distinct Value Estimation via Learning to Select and Fuse Estimators | 2025 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 37 | Statistical Estimators for Relational Algebra Expressions | 1988 | PODS | 0.00075597514 |
| 380 | Towards Estimation Error Guarantees for Distinct Values | 2000 | PODS | 0.00024943236 |
| 1,790 | Effective Use of Block-Level Sampling in Statistics Estimation | 2004 | SIGMOD | 0.00010529479 |
| 2,769 | FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation | 2021 | VLDB | 8.1512848e-05 |
| 3,016 | Adaptive and Big Data Scale Parallel Execution in Oracle | 2013 | VLDB | 7.7060968e-05 |
| 5,405 | ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads | 2024 | VLDB | 5.5243727e-05 |
| 7,611 | Learning to be a Statistician: Learned Estimator for Number of Distinct Values | 2022 | VLDB | 4.6920008e-05 |
| 7,915 | Efficient Approximate Algorithms for Empirical Entropy and Mutual Information | 2021 | SIGMOD | 4.6135329e-05 |
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