Greedy Approximation

Greedy Approximation is an approximation algorithm that belongs to the class of iterative heuristics and is characterized by making, at each step, the locally optimal choice with the intent of achieving a global near-optimal solution.

1.6K

Publications

142.7K

Citations

3.6K

Authors

1.1K

Institutions

Publications per year

2017–2026

383

Authors

3.6K

  1. VT
    Vladimir Temlyakov

    University of South Carolina, United States

    31 publications · 1.9K citations

    20

    h-index

  2. WW
    Weili Wu

    The University of Texas at Dallas, United States

    15 publications · 921 citations

    14

    h-index

  3. AK
    Andreas Krause

    ETH Zurich, Switzerland

    12 publications · 1.5K citations

    12

    h-index

  4. GC
    Guihai Chen

    Shanghai Jiao Tong University, China

    11 publications · 507 citations

    11

    h-index

  5. HD
    Haipeng Dai

    Nanjing University, China

    11 publications · 467 citations

    11

    h-index

1–5 of 3.6K

Venues

  1. arXiv (Cornell University)

    Repository · 66 publications · 2.3K citations

    22

    h-index

  2. Information Processing Letters

    21 publications · 946 citations

    17

    h-index

  3. SIAM Journal on Computing

    17 publications · 2.1K citations

    15

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 17 publications · 1.1K citations

    14

    h-index

  5. IEEE Transactions on Information Theory

    15 publications · 5.3K citations

    14

    h-index

1–5