Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries
Summary: Two DL-based estimators for multi-attribute selectivity: autoregressive density estimation of the joint distribution and a supervised predictor (range-query support). Tackles featurization, workload awareness, and dynamic data, delivering fast, accurate, compact estimates for many predicates at low selectivity. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shohedul Hasan (University of Texas)
- 2. Saravanan Thirumuruganathan (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 3. Jees Augustine (University of Texas)
- 4. Nick Koudas (University of Toronto)
- 5. Gautam Das (University of Texas)
BibTeX Citation
@inproceedings{hasan_sigmod20,
title = {{Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries}},
author = {Hasan, Shohedul and Thirumuruganathan, Saravanan and Augustine, Jees and Koudas, Nick and Das, Gautam},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3389741},
url = {https://dl.acm.org/doi/10.1145/3318464.3389741},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 41 of 41 citing papers.
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 7,440 | Cardinality Estimation of Approximate Substring Queries using Deep Learning | 2022 | VLDB |
| 2 | 2,523 | Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation | 2022 | VLDB |
| 3 | 5,457 | Sample-Efficient Cardinality Estimation Using Geometric Deep Learning | 2024 | VLDB |
| 4 | 3,212 | Efficiently Approximating Selectivity Functions using Low Overhead Regression Models | 2020 | VLDB |
| 5 | 1,511 | Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation | 2015 | SIGMOD |
| 6 | 10,014 | Selectivity Estimation for Queries Containing Predicates over Set-Valued Attributes | 2023 | SIGMOD |
| 7 | 287 | Selectivity Estimation using Probabilistic Models | 2001 | SIGMOD |
| 8 | 690 | Selectivity Estimation for Range Predicates using Lightweight Models | 2019 | VLDB |
| 9 | 8,297 | Consistent and Flexible Selectivity Estimation for High-Dimensional Data | 2021 | SIGMOD |
| 10 | 9,365 | Deep Query Optimization | 2019 | SIGMOD |