Space Complexity Of Graph Problems

Space Complexity of Graph Problems is a theoretical construct in computational complexity theory that characterizes the minimal amount of memory space required by an algorithm to solve graph-theoretic decision or optimization problems as a function of the input graph's size.

237

Publications

13.1K

Citations

477

Authors

270

Institutions

Publications per year

2017–2026

31

Authors

477

  1. IF
    Irene Finocchi

    Sapienza University of Rome, Italy

    5 publications · 163 citations

    5

    h-index

  2. AM
    Andrew McGregor

    University of Massachusetts Amherst, United States

    4 publications · 333 citations

    4

    h-index

  3. DE
    David Eppstein

    University of California, Irvine, United States

    4 publications · 139 citations

    4

    h-index

  4. SD
    Samir Datta

    Loughborough University, United Kingdom

    4 publications · 97 citations

    4

    h-index

  5. AW
    Avi Wigderson

    Hebrew University of Jerusalem, Israel

    4 publications · 198 citations

    4

    h-index

1–5 of 477

Venues

  1. SIAM Journal on Computing

    15 publications · 2K citations

    13

    h-index

  2. Algorithmica

    13 publications · 568 citations

    13

    h-index

  3. Discrete Applied Mathematics

    17 publications · 353 citations

    12

    h-index

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

    Repository · 11 publications · 302 citations

    11

    h-index

  5. arXiv (Cornell University)

    Repository · 11 publications · 183 citations

    10

    h-index

1–5