Fine-Grained Complexity Analysis of Queries: From Decision to Counting and Enumeration
Summary: Survey of fine-grained complexity for query answering that unifies decision, counting, and enumeration tasks, presenting algorithmic techniques, complexity measures and conditional lower bounds. Emphasizes consequences for aggregation and probabilistic databases, and enumeration trade-offs. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Arnaud Durand (University of Paris)
BibTeX Citation
@inproceedings{durand_pods20,
address = {New York, NY, USA},
series = {{PODS} '20},
title = {{Fine-Grained Complexity Analysis of Queries: From Decision to Counting and Enumeration}},
url = {https://dl.acm.org/doi/10.1145/3375395.3389130},
doi = {10.1145/3375395.3389130},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Durand, Arnaud},
year = {2020}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,985 | Change Propagation Without Joins | 2023 | VLDB | 6.412102e-05 |
| 5,593 | Beyond Equi-joins: Ranking, Enumeration and Factorization | 2021 | VLDB | 6.1552328e-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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