Approximation Complexity

Approximation Complexity is a computational complexity measure that characterizes the inherent difficulty of approximating optimal solutions to NP-hard problems within guaranteed performance bounds, distinguishing it from exact complexity by focusing on the trade-off between solution quality and computational tractability.

471

Publications

32.5K

Citations

815

Authors

387

Institutions

Publications per year

2017–2026

62

Authors

815

  1. SA
    Sanjeev Arora

    Princeton University, United States

    10 publications · 3.2K citations

    10

    h-index

  2. ID
    Irit Dinur

    Weizmann Institute of Science, Israel

    8 publications · 1.2K citations

    8

    h-index

  3. UF
    Uriel Feige

    Weizmann Institute of Science, Israel

    8 publications · 4.3K citations

    8

    h-index

  4. GJ
    Gerhard J. Woeginger

    Graz University of Technology, Austria

    7 publications · 374 citations

    7

    h-index

  5. JN
    Joseph Naor

    Technion – Israel Institute of Technology, Israel

    7 publications · 453 citations

    7

    h-index

1–5 of 815

Venues

  1. SIAM Journal on Computing

    25 publications · 2.3K citations

    21

    h-index

  2. arXiv (Cornell University)

    Repository · 27 publications · 609 citations

    15

    h-index

  3. Theoretical Computer Science

    14 publications · 604 citations

    12

    h-index

  4. Mathematical Programming

    12 publications · 825 citations

    12

    h-index

  5. Journal of the ACM

    JACM · 11 publications · 5.3K citations

    11

    h-index

1–5