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@COMMENT This file came from Kuldeep S. Meel's publication pages at
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@inproceedings{CVM22,
  title={Distinct Elements in Streams: An Algorithm for the (Text) Book},
  author={Chakraborty, Sourav and Vinodchandran, N. V. and Meel, Kuldeep S.},
  nameorder={random},
  bib2html_pubtype={Refereed Conference},
  year={2022},
  month=aug,
  booktitle=ESA,
  bib2html_rescat={Data Streams},
  abstract={
    Given a data stream of m elements, the Distinct Elements problem is to
    estimate the number of distinct elements in a stream.
    Distinct Elements has been a subject of theoretical and empirical
    investigations over the past four decades resulting in space optimal
    algorithms for it.
    All the current state-of-the-art algorithms are, however, beyond the reach
    of an undergraduate textbook owing to their reliance on the usage of notions
    such as pairwise independence and universal hash functions. We present a
    simple, intuitive, sampling-based space-efficient algorithm whose
    description and the proof are accessible to undergraduates with the
    knowledge of basic probability theory.
  },
  note={Highlighted in Donald Knuth's note on the paper},
  bib2html_dl_pdf={../Papers/esa22.pdf},
}