Kernel Lower Bounds

Kernel Lower Bounds is a theoretical framework in parameterized complexity that establishes limits on the size of kernels by proving that certain problems cannot admit polynomial or smaller kernelizations under widely believed complexity-theoretic assumptions.

298

Publications

14.3K

Citations

505

Authors

302

Institutions

Publications per year

2017–2026

63

Authors

505

  1. SK
    Stefan Kratsch

    Utrecht University, Netherlands

    9 publications · 573 citations

    9

    h-index

  2. AY
    Anders Yeo

    Royal Holloway University of London, United Kingdom

    8 publications · 481 citations

    8

    h-index

  3. BM
    Bart M. P. Jansen

    Utrecht University, Netherlands

    7 publications · 285 citations

    7

    h-index

  4. EB
    E. B. Davies

    King's College London, United Kingdom

    7 publications · 593 citations

    7

    h-index

  5. ST
    Stéphan Thomassé

    Centre National de la Recherche Scientifique, France

    7 publications · 562 citations

    7

    h-index

1–5 of 505

Venues

  1. arXiv (Cornell University)

    Repository · 18 publications · 548 citations

    12

    h-index

  2. Journal of Functional Analysis

    8 publications · 637 citations

    8

    h-index

  3. ACM Transactions on Algorithms

    TALG · 6 publications · 476 citations

    6

    h-index

  4. The Annals of Statistics

    6 publications · 829 citations

    6

    h-index

  5. Theoretical Computer Science

    6 publications · 461 citations

    6

    h-index

1–5