Optimality and Scalability in Lattice Histogram Construction
Summary: Dynamic-programming to construct an optimal lattice histogram (LH) under a max-error bound. A scalable greedy method delivers near-optimal accuracy with far lower time/space, applicable to space-bounded problems; experiments on real data show strong performance. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Panagiotis Karras (National University of Singapore)
BibTeX Citation
@article{karras_vldb09,
title = {{Optimality and Scalability in Lattice Histogram Construction}},
author = {Karras, Panagiotis},
journal = {PVLDB},
series = {{VLDB} '09},
doi = {10.14778/1687627.1687703},
url = {https://doi.org/10.14778/1687627.1687703},
year = {2009}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,957 | Efficient Haar+ Synopsis Construction for the Maximum Absolute Error Measure | 2018 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 19 of 19 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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