Randomized Sketching

Randomized Sketching is a probabilistic dimensionality reduction technique in streaming algorithms that compactly summarizes high-dimensional data streams into a low-dimensional randomized sketch, preserving key structural properties with high probability while using limited memory and computational resources.

37

Publications

2.4K

Citations

93

Authors

49

Institutions

Publications per year

2017–2026

10

Authors

93

  1. DP
    David P. Woodruff

    IBM Research - Almaden, United States

    5 publications · 254 citations

    5

    h-index

  2. RK
    Robert Krauthgamer

    Weizmann Institute of Science, Israel

    3 publications · 167 citations

    3

    h-index

  3. AA
    Alexandr Andoni

    Microsoft (United States), United States

    3 publications · 167 citations

    3

    h-index

  4. MK
    Michael Kapralov

    Stanford University, United States

    3 publications · 168 citations

    3

    h-index

  5. SP
    Shiva Prasad Kasiviswanathan

    Samsung (United States), United States

    2 publications · 61 citations

    2

    h-index

1–5 of 93

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 238 citations

    8

    h-index

  2. International Conference on Machine Learning

    Conference · 2 publications · 24 citations

    2

    h-index

  3. HAL (Le Centre pour la Communication Scientifique Directe)

    Repository · 1 publications · 16 citations

    1

    h-index

  4. Nature Computational Science

    1 publications · 43 citations

    1

    h-index

  5. Journal of Machine Learning Research

    JMLR · 1 publications · 30 citations

    1

    h-index

1–5