Dynamic Multidimensional Histograms
Summary: Dynamic multidimensional histograms for continuous streams; a compact dynamic summary tracks distribution and yields on-demand accurate histograms. Algorithms give approximate guarantees on histogram quality; evaluation on real data validates tradeoffs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nitin Thaper (Massachusetts Institute of Technology)
- 2. Sudipto Guha (University of Pennsylvania)
- 3. Piotr Indyk (Massachusetts Institute of Technology)
- 4. Nick Koudas (AT&T)
BibTeX Citation
@inproceedings{thaper_sigmod02,
title = {{Dynamic Multidimensional Histograms}},
author = {Thaper, Nitin and Guha, Sudipto and Indyk, Piotr and Koudas, Nick},
series = {{SIGMOD} '02},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/564691.564741},
url = {https://dl.acm.org/doi/10.1145/564691.564741},
year = {2002}
}
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