A faster FPRAS for #NFA
Summary: Presents a faster FPRAS for #NFA, reducing per-state samples to polylog(m) and Õ(n^4/ε^2); time is Õ((m^2 n^10 + m^3 n^6)/ε^4 · log^2(1/δ)). Uses weaker invariants and total-variation closeness to uniform, pushing toward practical approximate #NFA tools. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Kuldeep S. Meel (University of Toronto)
- 2. Sourav Chakraborty (Indian Statistical Institute)
- 3. Umang Mathur (National University of Singapore)
BibTeX Citation
@inproceedings{meel_pods24,
address = {New York, NY, USA},
series = {{PODS} '24},
title = {{A faster FPRAS for \#NFA}},
url = {https://dl.acm.org/doi/10.1145/3651613},
doi = {10.1145/3651613},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Meel, Kuldeep S. and Chakraborty, Sourav and Mathur, Umang},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,738 | Towards Practical FPRAS for #NFA: Exploiting the Power of Dependence | 2025 | PODS | 5.0723324e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,485 | Efficient Logspace Classes for Enumeration, Counting, and Uniform Generation | 2019 | PODS | 7.3562072e-05 |
| 7,353 | Probabilistic Query Evaluation: The Combined FPRAS Landscape | 2023 | PODS | 5.6230428e-05 |
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