Parallel Approximation Algorithms For Geometry

Parallel Approximation Algorithms for Geometry is a computational framework within algorithmic geometry that employs parallel processing to efficiently compute approximate solutions to geometric problems, distinguished by its focus on achieving near-optimal results in reduced time through concurrent computation.

21

Publications

1.3K

Citations

53

Authors

24

Institutions

Publications per year

2017–2026

2

Authors

53

  1. MT
    Michael T. Goodrich

    Johns Hopkins University, United States

    3 publications · 170 citations

    3

    h-index

  2. MJ
    Mikhail J. Atallah

    Purdue University West Lafayette, United States

    2 publications · 121 citations

    2

    h-index

  3. HH
    Hugues Hoppe

    Microsoft Research (United Kingdom), United Kingdom

    1 publications · 164 citations

    1

    h-index

  4. TT
    Tiow-Seng Tan

    National University of Singapore, Singapore

    1 publications · 24 citations

    1

    h-index

  5. GL
    Gary L. Miller

    Carnegie Mellon University, United States

    1 publications · 49 citations

    1

    h-index

1–5 of 53

Venues

  1. Proceedings of the International Conference on Parallel Processing

    Conference · 3 publications · 88 citations

    3

    h-index

  2. Computer Graphics Forum

    2 publications · 182 citations

    2

    h-index

  3. Computers & Graphics

    2 publications · 344 citations

    2

    h-index

  4. International Conference on Machine Learning

    Conference · 1 publications · 16 citations

    1

    h-index

  5. Information Processing Letters

    1 publications · 79 citations

    1

    h-index

1–5