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Understanding Cardinality Estimation using Entropy Maximization

Summary: Principled MaxEnt framework for cardinality estimation: treat given query statistics as constraints on a distribution over possible worlds and pick the maximum-entropy model. Develops the mathematical tools to apply MaxEnt to predict conjunctive-query cardinalities, enabling systematic inference from arbitrary statistical assertions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1506
Venue
PODS
Year
2010
Pagerank
6.0636893e-05
Overall Rank
5,860 | 59.80%
DOI
10.1145/1807085.1807095

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{re_pods10,
        address = {New York, NY, USA},
        series = {{PODS} '10},
        title = {{Understanding Cardinality Estimation using Entropy Maximization}},
        url = {https://dl.acm.org/doi/10.1145/1807085.1807095},
        doi = {10.1145/1807085.1807095},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Ré, Christopher and Suciu, Dan},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
1,170 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00011827259
2,369 Data Generation using Declarative Constraints 2011 SIGMOD 8.682429e-05
8,191 Probabilistic Database Summarization for Interactive Data Exploration 2017 VLDB 5.4699738e-05
10,151 Coresets for Robust Query Optimization 2026 PODS 5.093636e-05
12,183 Online Ordering of Overlapping Data Sources 2014 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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