Randomized Query Complexity

Randomized Query Complexity is a complexity measure in computational complexity theory that quantifies the minimum expected number of queries a randomized algorithm must make to compute a function correctly with bounded error probability.

50

Publications

1.9K

Citations

96

Authors

54

Institutions

Publications per year

2017–2026

5

Authors

96

  1. MS
    Márió Szegedy

    Rutgers, The State University of New Jersey, United States

    3 publications · 196 citations

    3

    h-index

  2. IN
    Ilan Newman

    University of Haifa, Israel

    3 publications · 195 citations

    3

    h-index

  3. AA
    Andris Ambainis

    University of Latvia, Latvia

    3 publications · 109 citations

    3

    h-index

  4. NN
    Noam Nisan

    Hebrew University of Jerusalem, Israel

    3 publications · 58 citations

    3

    h-index

  5. MS
    Miklós Sántha

    Centre National de la Recherche Scientifique, France

    2 publications · 54 citations

    2

    h-index

1–5 of 96

Venues

  1. SIAM Journal on Computing

    6 publications · 531 citations

    6

    h-index

  2. arXiv (Cornell University)

    Repository · 5 publications · 90 citations

    5

    h-index

  3. Information Processing Letters

    3 publications · 55 citations

    3

    h-index

  4. Theoretical Computer Science

    2 publications · 70 citations

    2

    h-index

  5. Symposium on Discrete Algorithms

    Conference · 2 publications · 76 citations

    2

    h-index

1–5