Randomized Graph Algorithms

Randomized Graph Algorithms is a class of graph algorithms that incorporate randomness into their decision-making processes to achieve improved average-case performance, simplicity, or scalability in solving graph-theoretic problems.

748

Publications

39K

Citations

1.2K

Authors

500

Institutions

Publications per year

2017–2026

127

Authors

1.2K

  1. AF
    Alan Frieze

    Carnegie Mellon University, United States

    27 publications · 1.4K citations

    19

    h-index

  2. NA
    Noga Alon

    Tel Aviv University, Israel

    23 publications · 2.6K citations

    17

    h-index

  3. MG
    Mohsen Ghaffari

    ETH Zurich, Switzerland

    15 publications · 658 citations

    14

    h-index

  4. UF
    Uriel Feige

    Weizmann Institute of Science, Israel

    14 publications · 1.1K citations

    12

    h-index

  5. SP
    Seth Pettie

    University of Michigan, United States

    12 publications · 655 citations

    12

    h-index

1–5 of 1.2K

Venues

  1. Random Structures and Algorithms

    46 publications · 2.9K citations

    27

    h-index

  2. SIAM Journal on Computing

    39 publications · 2.7K citations

    25

    h-index

  3. arXiv (Cornell University)

    Repository · 28 publications · 843 citations

    15

    h-index

  4. Discrete Applied Mathematics

    20 publications · 895 citations

    15

    h-index

  5. COMBINATORICA

    17 publications · 934 citations

    15

    h-index

1–5