Matrix Sketching

Matrix sketching is a dimensionality reduction technique that, as a member of the class of randomized approximation methods for large-scale linear algebra, computes a compact representation of a matrix by applying random projections or sampling to preserve key spectral properties with sublinear space and time complexity.

60

Publications

2.8K

Citations

138

Authors

74

Institutions

Publications per year

2017–2026

24

Authors

138

  1. DP
    David P. Woodruff

    IBM Research - Almaden, United States

    12 publications · 837 citations

    11

    h-index

  2. EL
    Edo Liberty

    Yahoo (United States), United States

    6 publications · 487 citations

    6

    h-index

  3. JM
    Jeff M. Phillips

    University of Utah, United States

    5 publications · 245 citations

    5

    h-index

  4. MG
    Mina Ghashami

    University of Utah, United States

    5 publications · 245 citations

    5

    h-index

  5. VC
    Volkan Cevher

    École Polytechnique Fédérale de Lausanne, Switzerland

    4 publications · 123 citations

    4

    h-index

1–5 of 138

Venues

  1. arXiv (Cornell University)

    Repository · 14 publications · 382 citations

    12

    h-index

  2. 3

    h-index

  3. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 2 publications · 49 citations

    2

    h-index

  4. CaltechAUTHORS (California Institute of Technology)

    Repository · 1 publications · 28 citations

    1

    h-index

  5. ArXiv.org

    Repository · 1 publications · 22 citations

    1

    h-index

1–5