Linear Solver Convergence

Linear Solver Convergence is the property of an iterative algorithm to approach a solution of a system of linear equations within a prescribed tolerance as the number of iterations increases, characterized by the diminishing residual error according to a specific convergence criterion.

117

Publications

9.4K

Citations

235

Authors

121

Institutions

Publications per year

2017–2026

34

Authors

235

  1. DN
    Deanna Needell

    University of California, Los Angeles, United States

    3 publications · 94 citations

    3

    h-index

  2. YB
    Yunier Bello-Cruz

    Universidade Federal de Goiás, Brazil

    3 publications · 103 citations

    3

    h-index

  3. ZL
    Zhi‐Quan Luo

    University of Minnesota, United States

    3 publications · 958 citations

    3

    h-index

  4. MH
    Mingyi Hong

    University of Minnesota, United States

    3 publications · 853 citations

    3

    h-index

  5. JL
    Julien Langou

    University of Tennessee at Knoxville, United States

    3 publications · 90 citations

    3

    h-index

1–5 of 235

Venues

  1. SIAM Journal on Matrix Analysis and Applications

    10 publications · 642 citations

    10

    h-index

  2. Mathematical Programming

    6 publications · 857 citations

    6

    h-index

  3. SIAM Journal on Scientific Computing

    6 publications · 562 citations

    6

    h-index

  4. arXiv (Cornell University)

    Repository · 7 publications · 439 citations

    6

    h-index

  5. SIAM Journal on Numerical Analysis

    5 publications · 286 citations

    5

    h-index

1–5