Randomized Linear Algebra

Randomized Linear Algebra is a computational framework within numerical linear algebra that employs randomized algorithms to approximate matrix computations, distinguishing itself by leveraging probabilistic methods to achieve efficiency and scalability in large-scale problems.

205

Publications

13K

Citations

352

Authors

190

Institutions

Publications per year

2017–2026

76

Authors

352

  1. DP
    David P. Woodruff

    IBM Research - Almaden, United States

    9 publications · 566 citations

    9

    h-index

  2. PD
    Petros Drineas

    Rensselaer Polytechnic Institute, United States

    8 publications · 434 citations

    8

    h-index

  3. MT
    Mark Tygert

    Yale University, United States

    7 publications · 1.9K citations

    7

    h-index

  4. PM
    Per‐Gunnar Martinsson

    University of Colorado Boulder, United States

    7 publications · 1.1K citations

    7

    h-index

  5. MW
    Michael W. Mahoney

    University of California, Berkeley, United States

    6 publications · 574 citations

    6

    h-index

1–5 of 352

Venues

  1. arXiv (Cornell University)

    Repository · 25 publications · 772 citations

    15

    h-index

  2. Linear Algebra and its Applications

    10 publications · 524 citations

    10

    h-index

  3. SIAM Journal on Matrix Analysis and Applications

    9 publications · 1.5K citations

    9

    h-index

  4. 5

    h-index

  5. Applied Mathematics Letters

    4 publications · 196 citations

    5

    h-index

1–5