Randomness Extractors

A Randomness Extractor is a deterministic algorithm that belongs to the class of computational procedures designed to distill nearly uniform random bits from weak sources of randomness, distinguished by its ability to achieve this extraction with minimal reliance on external randomness or additional assumptions about the source distribution.

91

Publications

5.9K

Citations

142

Authors

81

Institutions

Publications per year

2017–2026

9

Authors

142

  1. AW
    Avi Wigderson

    Hebrew University of Jerusalem, Israel

    12 publications · 903 citations

    12

    h-index

  2. SV
    Salil Vadhan

    Harvard University Press, United States

    11 publications · 1.1K citations

    11

    h-index

  3. DZ
    David Zuckerman

    The University of Texas at Austin, United States

    9 publications · 976 citations

    9

    h-index

  4. RS
    Ronen Shaltiel

    University of Haifa, Israel

    9 publications · 588 citations

    9

    h-index

  5. ZD
    Zeev Dvir

    Princeton University, United States

    6 publications · 273 citations

    6

    h-index

1–5 of 142

Venues

  1. SIAM Journal on Computing

    6 publications · 501 citations

    6

    h-index

  2. IEEE Transactions on Information Theory

    5 publications · 161 citations

    5

    h-index

  3. arXiv (Cornell University)

    Repository · 5 publications · 106 citations

    5

    h-index

  4. Journal of the ACM

    JACM · 3 publications · 499 citations

    3

    h-index

  5. Physical Review A

    PRA · 3 publications · 305 citations

    3

    h-index

1–5