Learning and Verifying Quantified Boolean Queries by Example
Summary: Analyzes membership-query complexity for learning and verifying qhorn — conjunctions of quantified Horn expressions — via answer/non-answer questions. Presents optimal polynomial-time and polynomial-question algorithms for two qhorn subclasses under constant-bounded causal density. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Azza Abouzied (Yale University)
- 2. Dana Angluin (Yale University)
- 3. Christos Papadimitriou (University of California Berkeley)
- 4. Joseph M. Hellerstein (University of California Berkeley)
- 5. Avi Silberschatz (Yale University)
BibTeX Citation
@inproceedings{abouzied_pods13,
address = {New York, NY, USA},
series = {{PODS} '13},
title = {{Learning and Verifying Quantified Boolean Queries by Example}},
url = {https://dl.acm.org/doi/10.1145/2463664.2465220},
doi = {10.1145/2463664.2465220},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Abouzied, Azza and Angluin, Dana and Papadimitriou, Christos and Hellerstein, Joseph M. and Silberschatz, Avi},
year = {2013}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 517 | Query by Output | 2009 | SIGMOD | 0.00017169735 |
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