Multivariate Parameterized Algorithms

Multivariate Parameterized Algorithms is a parameterized algorithmic framework that simultaneously incorporates multiple independent parameters to analyze computational tractability, distinguishing itself from univariate approaches by enabling a more granular complexity assessment through the joint dependency on several structural or numerical input measures.

4

Publications

327

Citations

9

Authors

5

Institutions

Publications per year

2017–2026

0

Authors

9

  1. RN
    Rolf Niedermeier

    Technische Universität Berlin, Germany

    3 publications · 223 citations

    3

    h-index

  2. FR
    Frances Rosamond

    University of Newcastle Australia, Australia

    1 publications · 104 citations

    1

    h-index

  3. MR
    Michael R. Fellows

    University of Victoria, Canada

    1 publications · 104 citations

    1

    h-index

  4. LB
    Laurent Bulteau

    Centre National de la Recherche Scientifique, France

    1 publications · 35 citations

    1

    h-index

  5. BM
    Bart M. P. Jansen

    Utrecht University, Netherlands

    1 publications · 104 citations

    1

    h-index

1–5 of 9

Venues

  1. European Journal of Combinatorics

    1 publications · 104 citations

    1

    h-index

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

    Repository · 1 publications · 117 citations

    1

    h-index

1–2