Aeris Filter: A Strongly and Monotonically Adaptive Range Filter
Summary: Aeris Filter: expandable range filter with strong guarantees against both spatial and temporal skew. Key idea: monotonic adaptivity—never forgets prior false positives—via novel encoding, plus deamortized on-disk expansion; up to 10x lower FPR and 1.5–8x higher throughput on adversarial workloads. (summarized by gpt-5.4-mini on Apr 11 2026)
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Authors
- 1. Yuvaraj Chesetti (Northeastern University)
- 2. Navid Eslami (University of Toronto)
- 3. Huanchen Zhang (Tsinghua University)
- 4. Niv Dayan (University of Toronto)
- 5. Prashant Pandey (Northeastern University)
BibTeX Citation
@inproceedings{chesetti_sigmod26,
title = {{Aeris Filter: A Strongly and Monotonically Adaptive Range Filter}},
author = {Chesetti, Yuvaraj and Eslami, Navid and Zhang, Huanchen and Dayan, Niv and Pandey, Prashant},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786621},
url = {https://dl.acm.org/doi/10.1145/3786621},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,295 | Sublime: Sublinear Error & Space for Unbounded Skewed Streams | 2026 | SIGMOD | 5.093636e-05 |
| 10,307 | Zeno Filter: To Infinity in Tiny Steps | 2026 | SIGMOD | 5.093636e-05 |
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