Adaptive Execution of Variable-Accuracy Functions
Summary: VAOs expose compute-accuracy tradeoffs for modeling UDFs, letting queries stop at the needed precision. Prototype on financial queries over real bond data shows adaptive, cost-aware evaluation in common operators. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Matthew Denny (University of California Berkeley)
- 2. Michael J. Franklin (University of California Berkeley)
BibTeX Citation
@article{denny_vldb06,
title = {{Adaptive Execution of Variable-Accuracy Functions}},
author = {Denny, Matthew and Franklin, Michael J.},
journal = {PVLDB},
series = {{VLDB} '06},
pages = {547--558},
doi = {10.5555/1182635.1182690},
url = {https://doi.org/10.5555/1182635.1182690},
year = {2006}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,646 | Supporting User-Defined Functions on Uncertain Data | 2013 | VLDB | 5.3928856e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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