Parallel Optimization

Parallel Optimization is a computational strategy within optimization algorithms that belongs to the class of distributed or concurrent methods, distinguished by its ability to simultaneously evaluate multiple operations or search directions across different processing units to accelerate convergence in machine learning problems.

1.1K

Publications

74.9K

Citations

3K

Authors

988

Institutions

Publications per year

2017–2026

348

Authors

3K

  1. PR
    Peter Richtárik

    University of Edinburgh, United Kingdom

    14 publications · 1.3K citations

    13

    h-index

  2. MT
    Martin Takáč

    Lehigh University, United States

    12 publications · 1K citations

    11

    h-index

  3. GS
    Gesualdo Scutari

    Sapienza University of Rome, Italy

    12 publications · 883 citations

    11

    h-index

  4. FF
    Francisco Facchinei

    Sapienza University of Rome, Italy

    11 publications · 777 citations

    10

    h-index

  5. JP
    Jeng‐Shyang Pan

    Shandong University of Science and Technology, China

    8 publications · 461 citations

    8

    h-index

1–5 of 3K

Venues

  1. arXiv (Cornell University)

    Repository · 99 publications · 10.1K citations

    36

    h-index

  2. SIAM Journal on Optimization

    23 publications · 1.6K citations

    18

    h-index

  3. Parallel Computing

    24 publications · 1.6K citations

    17

    h-index

  4. Structural and Multidisciplinary Optimization

    18 publications · 795 citations

    14

    h-index

  5. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 14 publications · 869 citations

    13

    h-index

1–5