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@inproceedings{PVBM21,
  title={Model Counting meets F0 Estimation},
  author={
    Pavan, A. and Vinodchandran, N.V. and Bhattacharya, Arnab and Meel, Kuldeep
    S.
  },
  booktitle=PODS,
  nameorder={random},
  bib2html_rescat={Counting, Data Streams},
  bib2html_dl_pdf={../Papers/pods21-pvbm.pdf},
  bib2html_pubtype={Refereed Conference,Award Winner},
  year={2021},
  month=jun,
  note={CACM Research Highlight and 2021 ACM SIGMOD Research Highlight},
  abstract={
    Constraint satisfaction problems (CSP's) and data stream models are two
    powerful abstractions to capture a wide variety of problems arising in
    different domains of computer science. Developments in the two communities
    have mostly occurred independently and with little interaction between them.
    In this work, we seek to investigate whether bridging the seeming
    communication gap between the two communities may pave the way to richer
    fundamental insights. To this end, we focus on two foundational problems:
    model counting for CSP's and computation of zeroth frequency moments $(F_0)$
    for data streams.
    Our investigations lead us to observe striking similarity in the core
    techniques employed in the algorithmic frameworks that have evolved
    separately for model counting and $F_0$ computation. We design a recipe for
    translation of algorithms developed for $F_0$ estimation to that of model
    counting, resulting in new
    algorithms for model counting. We then observe that algorithms in the
    context of distributed streaming can be transformed to distributed
    algorithms for model counting. We next turn our attention to viewing
    streaming from the lens of counting and show that framing $F_0$ estimation
    as a special case of \#DNF counting allows us to obtain a general recipe for
    a rich class of streaming problems, which had been subjected to
    case-specific analysis in prior works. In particular, our view yields a
    state-of-the art algorithm for multidimensional range efficient $F_0$
    estimation with a simpler analysis.
  },
}