Algorithmic Lower Bounds

Algorithmic Lower Bounds is a theoretical construct in computer science that establishes the minimum computational resources, such as time or space, required by any algorithm to solve a given problem, thereby providing a fundamental limit against which algorithmic efficiency can be measured.

398

Publications

18.1K

Citations

735

Authors

332

Institutions

Publications per year

2017–2026

86

Authors

735

  1. PB
    Paul Beame

    University of Washington, United States

    10 publications · 912 citations

    10

    h-index

  2. TP
    Toniann Pitassi

    University of Toronto, Canada

    8 publications · 687 citations

    8

    h-index

  3. FV
    Fedor V. Fomin

    University of Bergen, Norway

    5 publications · 229 citations

    5

    h-index

  4. SP
    Seth Pettie

    University of Michigan, United States

    5 publications · 208 citations

    5

    h-index

  5. MP
    Mihai Pǎtraşcu

    AT&T (United States), United States

    5 publications · 143 citations

    5

    h-index

1–5 of 735

Venues

  1. arXiv (Cornell University)

    Repository · 38 publications · 996 citations

    18

    h-index

  2. SIAM Journal on Computing

    16 publications · 805 citations

    15

    h-index

  3. Mathematical Programming

    8 publications · 449 citations

    8

    h-index

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

    Repository · 8 publications · 155 citations

    8

    h-index

  5. Journal of the ACM

    JACM · 8 publications · 512 citations

    8

    h-index

1–5