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An FPRAS for Model Counting for Non-Deterministic Read-Once Branching Programs

An FPRAS for Model Counting for Non-Deterministic Read-Once Branching Programs .
Kuldeep S. Meel ⓡ Alexis de Colnet.
In Proceedings of the International Conference on Database Theory (ICDT), March 2025.

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Abstract

Non-deterministic read-once branching programs, also known as non-deterministic free binary decision diagrams (nFBDD), are a fundamental data structure in computer science for representing Boolean functions. In this paper, we focus on #nFBDD, the problem of model counting for non-deterministic read-once branching programs. The #nFBDD problem is #P-hard, and it is known that there exists a quasi-polynomial randomized approximation scheme for #nFBDD. In this paper, we provide the first FPRAS for #nFBDD. Our result relies on the introduction of new analysis techniques that focus on bounding the dependence of samples.

BibTeX

@inproceedings{MdC25,
  title={
    An FPRAS for Model Counting for Non-Deterministic Read-Once Branching
    Programs
  },
  booktitle=ICDT,
  author={Meel, Kuldeep S. and de Colnet, Alexis},
  abstract={
    Non-deterministic read-once branching programs, also known as
    non-deterministic free binary decision diagrams (nFBDD), are a fundamental
    data structure in computer science for representing Boolean functions. In
    this paper, we focus on #nFBDD, the problem of model counting for
    non-deterministic read-once branching programs. The #nFBDD problem is
    #P-hard, and it is known that there exists a quasi-polynomial randomized
    approximation scheme for #nFBDD. In this paper, we provide the first FPRAS
    for #nFBDD. Our result relies on the introduction of new analysis techniques
    that focus on bounding the dependence of samples.
  },
  year={2025},
  month=mar,
  bib2html_rescat={Counting},
  bib2html_pubtype={Refereed Conference},
  bib2html_dl_pdf={https://arxiv.org/abs/2406.16515},
  nameorder={random},
}

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