Sublinear-time Algorithms

Sublinear-Time Algorithms is a computational method that belongs to the class of randomized algorithms and is distinguished by its ability to solve problems in time asymptotically less than the input size, typically by exploiting probabilistic strategies to achieve efficient approximations or local inspections.

273

Publications

15.1K

Citations

520

Authors

214

Institutions

Publications per year

2017–2026

68

Authors

520

  1. RR
    Ronitt Rubinfeld

    Massachusetts Institute of Technology, United States

    15 publications · 1.1K citations

    14

    h-index

  2. DR
    Dana Ron

    Tel Aviv University, Israel

    9 publications · 352 citations

    9

    h-index

  3. PI
    Piotr Indyk

    Massachusetts Institute of Technology, United States

    9 publications · 568 citations

    9

    h-index

  4. TB
    Tuğkan Batu

    IBM Research - Almaden, United States

    7 publications · 653 citations

    7

    h-index

  5. CS
    C. Seshadhri

    Sandia National Laboratories California, United States

    6 publications · 97 citations

    6

    h-index

1–5 of 520

Venues

  1. SIAM Journal on Computing

    15 publications · 828 citations

    14

    h-index

  2. arXiv (Cornell University)

    Repository · 19 publications · 662 citations

    12

    h-index

  3. ACM Transactions on Algorithms

    TALG · 10 publications · 255 citations

    10

    h-index

  4. Algorithmica

    9 publications · 418 citations

    9

    h-index

  5. Journal of the ACM

    JACM · 8 publications · 955 citations

    8

    h-index

1–5