Dynamic Maintenance of Wavelet-Based Histograms
Summary: Dynamic maintenance of wavelet-based histograms via probabilistic counting and sampling enables fast online updates. The method preserves accuracy under distribution drift and scales to multidimensional histograms, outperforming standard update methods. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yossi Matias (Tel Aviv University)
- 2. Jeffrey Scott Vitter (Duke University)
- 3. Min Wang (IBM)
BibTeX Citation
@article{matias_vldb00,
title = {{Dynamic Maintenance of Wavelet-Based Histograms}},
author = {Matias, Yossi and Vitter, Jeffrey Scott and Wang, Min},
journal = {PVLDB},
series = {{VLDB} '00},
pages = {101--112},
year = {2000}
}
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