Approximate Range Searching

Approximate Range Searching is a computational geometry method that generalizes exact range searching by allowing approximate answers to queries, thereby relaxing the precision requirement to achieve improved efficiency in high-dimensional or large-scale datasets.

46

Publications

1.8K

Citations

103

Authors

52

Institutions

Publications per year

2017–2026

3

Authors

103

  1. DM
    David M. Mount

    University of Maryland, College Park, United States

    4 publications · 226 citations

    4

    h-index

  2. PA
    Peyman Afshani

    Aarhus University, Denmark

    3 publications · 74 citations

    3

    h-index

  3. BA
    Boris Aronov

    New York University, United States

    3 publications · 188 citations

    3

    h-index

  4. YT
    Yufei Tao

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 151 citations

    2

    h-index

  5. JZ
    J. Z. Sun

    IBM (United States), United States

    2 publications · 114 citations

    2

    h-index

1–5 of 103

Venues

  1. Computational Geometry

    5 publications · 211 citations

    5

    h-index

  2. Discrete & Computational Geometry

    3 publications · 73 citations

    3

    h-index

  3. Mathematics of Computation

    MCOM · 2 publications · 33 citations

    2

    h-index

  4. SIAM Journal on Computing

    2 publications · 142 citations

    2

    h-index

  5. 1

    h-index

1–5