Maximum Matching Approximation

Maximum Matching Approximation is a method in approximation algorithms that belongs to the class of greedy algorithms, differing by specifically addressing the problem of finding a matching in a graph that is guaranteed to be within a certain factor of the maximum possible size.

179

Publications

15.4K

Citations

329

Authors

189

Institutions

Publications per year

2017–2026

30

Authors

329

  1. SK
    Sanjeev Khanna

    University of Pennsylvania, United States

    11 publications · 448 citations

    11

    h-index

  2. SA
    Sepehr Assadi

    University of Pennsylvania, United States

    9 publications · 269 citations

    9

    h-index

  3. MM
    Morteza Monemizadeh

    University of Warwick, United Kingdom

    6 publications · 105 citations

    6

    h-index

  4. MH
    MohammadTaghi Hajiaghayi

    University of Maryland, College Park, United States

    6 publications · 133 citations

    6

    h-index

  5. MK
    Michael Kapralov

    Stanford University, United States

    6 publications · 382 citations

    6

    h-index

1–5 of 329

Venues

  1. arXiv (Cornell University)

    Repository · 15 publications · 327 citations

    12

    h-index

  2. Information Processing Letters

    12 publications · 777 citations

    10

    h-index

  3. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 9 publications · 166 citations

    9

    h-index

  4. Discrete Mathematics

    5 publications · 196 citations

    5

    h-index

  5. Theoretical Computer Science

    5 publications · 139 citations

    5

    h-index

1–5