Zeno Filter: To Infinity in Tiny Steps
Summary: Zeno Filter is an expandable probabilistic filter that avoids conventional 2× growth via subdoubling “stretching” and expands in place through succinct indirection. It cuts space usage by up to 60% while preserving existing filters’ speed and accuracy. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Hyuhng Min Kim (University of Toronto)
- 2. Navid Eslami (University of Toronto)
- 3. Niv Dayan (University of Toronto)
BibTeX Citation
@inproceedings{kim_sigmod26,
title = {{Zeno Filter: To Infinity in Tiny Steps}},
author = {Kim, Hyuhng Min and Eslami, Navid and Dayan, Niv},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802128},
url = {https://dl.acm.org/doi/10.1145/3802128},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,295 | Sublime: Sublinear Error & Space for Unbounded Skewed Streams | 2026 | SIGMOD | 5.093636e-05 |
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Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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