Dynamic Order Statistics

Dynamic Order Statistics is a dynamic data structure that extends balanced binary search trees to efficiently support order-statistic operations, such as selecting the i-th smallest element and determining the rank of a given element, while allowing for dynamic insertions and deletions.

5

Publications

152

Citations

26

Authors

13

Institutions

Publications per year

2017–2026

1

Authors

26

  1. JS
    John Schneeloch

    Brookhaven National Laboratory, United States

    1 publications · 84 citations

    1

    h-index

  2. PA
    Peter Abbamonte

    University of Illinois Urbana-Champaign, United States

    1 publications · 84 citations

    1

    h-index

  3. AM
    Alejandra M. González-Mejía

    Environmental Protection Agency, United States

    1 publications · 18 citations

    1

    h-index

  4. SA
    Sean A. Hartnoll

    Stanford University, United States

    1 publications · 84 citations

    1

    h-index

  5. JT
    John T. Robinson

    IBM Research - Thomas J. Watson Research Center, United States

    1 publications · 16 citations

    1

    h-index

1–5 of 26

Venues

  1. Science Advances

    1 publications · 84 citations

    1

    h-index

  2. The Journal of Physical Chemistry B

    1 publications · 23 citations

    1

    h-index

  3. Environmental Science & Technology

    1 publications · 18 citations

    1

    h-index

  4. 1

    h-index

1–4