Fine-grained Complexity

Fine-Grained Complexity is a subfield of computational complexity theory that classifies computational problems based on their precise running time dependencies, distinguishing itself by aiming to establish tight conditional lower bounds under conjectured hardness assumptions of well-studied problems such as the Strong Exponential Time Hypothesis or the 3SUM conjecture.

45

Publications

1K

Citations

110

Authors

71

Institutions

Publications per year

2017–2026

26

Authors

110

  1. AA
    Amir Abboud

    Stanford University, United States

    4 publications · 78 citations

    4

    h-index

  2. KB
    Karl Bringmann

    Max Planck Institute for Informatics, Germany

    4 publications · 68 citations

    4

    h-index

  3. AB
    Artūrs Bačkurs

    Massachusetts Institute of Technology, United States

    3 publications · 59 citations

    3

    h-index

  4. SZ
    Shai Zeevi

    Technion – Israel Institute of Technology, Israel

    2 publications · 34 citations

    2

    h-index

  5. PM
    Pasin Manurangsi

    University of California, Berkeley, United States

    2 publications · 47 citations

    2

    h-index

1–5 of 110

Venues

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

    Repository · 11 publications · 202 citations

    11

    h-index

  2. arXiv (Cornell University)

    Repository · 4 publications · 55 citations

    4

    h-index

  3. Assessing Writing

    2 publications · 78 citations

    2

    h-index

  4. ACM Transactions on Algorithms

    TALG · 2 publications · 31 citations

    2

    h-index

  5. Complexity

    1 publications · 16 citations

    1

    h-index

1–5