Inapproximability

Inapproximability is the theoretical property of certain optimization problems that establishes a lower bound on how closely their optimal solution can be approximated in polynomial time, assuming standard complexity-theoretic conjectures such as P ≠ NP.

296

Publications

21.5K

Citations

481

Authors

252

Institutions

Publications per year

2017–2026

39

Authors

481

  1. SK
    Subhash Khot

    Georgia Institute of Technology, United States

    15 publications · 1.8K citations

    14

    h-index

  2. VG
    Venkatesan Guruswami

    Carnegie Mellon University, United States

    12 publications · 610 citations

    11

    h-index

  3. JH
    Johan Håstad

    KTH Royal Institute of Technology, Sweden

    11 publications · 353 citations

    10

    h-index

  4. LT
    Luca Trevisan

    University of California, Berkeley, United States

    8 publications · 639 citations

    9

    h-index

  5. OS
    Ola Svensson

    École Polytechnique Fédérale de Lausanne, Switzerland

    7 publications · 388 citations

    7

    h-index

1–5 of 481

Venues

  1. SIAM Journal on Computing

    22 publications · 2.2K citations

    18

    h-index

  2. arXiv (Cornell University)

    Repository · 16 publications · 400 citations

    13

    h-index

  3. Theoretical Computer Science

    11 publications · 1.5K citations

    11

    h-index

  4. ACM Transactions on Algorithms

    TALG · 11 publications · 616 citations

    10

    h-index

  5. SIAM Journal on Discrete Mathematics

    7 publications · 621 citations

    7

    h-index

1–5