Halfspace Range Searching

Halfspace Range Searching is a range searching paradigm in computational geometry where the query region is defined by a halfspace, distinguishing it from other range searching methods by its use of linear inequalities to partition the space and retrieve points lying on one side of a hyperplane.

24

Publications

974

Citations

29

Authors

25

Institutions

Publications per year

2017–2026

0

Authors

29

  1. TM
    Timothy M. Chan

    University of Waterloo, Canada

    6 publications · 231 citations

    6

    h-index

  2. BC
    Bernard Chazelle

    Princeton University, United States

    4 publications · 155 citations

    4

    h-index

  3. PG
    Prosenjit Gupta

    University of Minnesota, United States

    2 publications · 36 citations

    2

    h-index

  4. HB
    Hervé Brönnimann

    New York University, United States

    2 publications · 68 citations

    2

    h-index

  5. PA
    Peyman Afshani

    Aarhus University, Denmark

    2 publications · 92 citations

    2

    h-index

1–5 of 29

Venues

  1. SIAM Journal on Computing

    6 publications · 222 citations

    6

    h-index

  2. Discrete & Computational Geometry

    4 publications · 144 citations

    4

    h-index

  3. Information Processing Letters

    1 publications · 94 citations

    1

    h-index

  4. Computational Geometry

    1 publications · 22 citations

    1

    h-index

  5. Symposium on Discrete Algorithms

    Conference · 1 publications · 12 citations

    1

    h-index

1–5