Efficient Searching with Linear Constraints (Extended Abstract)
Summary: External-memory data structures for reporting points satisfying a linear constraint a·x ∈ [α,β] in R^d, with focus on I/O cost. For d=2: first near-linear-space structure with optimal I/Os, plus a linear-size worst-case-efficient structure, space/query tradeoffs, and extensions to higher dimensions. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Pankaj K. Agarwal (Duke University)
- 2. Lars Arge (Duke University)
- 3. Jeff Erickson (Duke University)
- 4. Paolo G. Franciosa (Sapienza University)
- 5. Jeffrey Scott Vitter (Duke University)
BibTeX Citation
@inproceedings{agarwal_pods98,
address = {New York, NY, USA},
series = {{PODS} '98},
title = {{Efficient Searching with Linear Constraints (Extended Abstract)}},
url = {https://dl.acm.org/doi/10.1145/275487.275506},
doi = {10.1145/275487.275506},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Agarwal, Pankaj K. and Arge, Lars and Erickson, Jeff and Franciosa, Paolo G. and Vitter, Jeffrey Scott},
year = {1998}
}
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