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Global Optimization of Histograms

Summary: Global optimization of histograms across multiple attributes, allocating buckets adaptively to skew and usage to minimize error. DP and greedy algorithms versus equal-bucket baselines; results show large reductions, up to 100x for skewed data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3333
Venue
SIGMOD
Year
2001
Pagerank
0.00010057026
Overall Rank
1,668 | 88.56%
DOI
10.1145/375663.375687

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{jagadish_sigmod01,
        title = {{Global Optimization of Histograms}},
        author = {Jagadish, H.V. and Jin, Hui and Ooi, Beng Chin and Tan, Kian-Lee},
        series = {{SIGMOD} '01},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/375663.375687},
        url = {https://dl.acm.org/doi/10.1145/375663.375687},
        year = {2001}
}

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