Randomized Optimization

Randomized Optimization is an optimization method that belongs to the class of unconstrained optimization techniques, distinguished by its use of stochastic processes to guide the search for optimal solutions, thereby enabling escape from local minima and exploration of complex, high-dimensional landscapes.

291

Publications

17.4K

Citations

622

Authors

275

Institutions

Publications per year

2017–2026

88

Authors

622

  1. PR
    Peter Richtárik

    University of Edinburgh, United Kingdom

    10 publications · 323 citations

    10

    h-index

  2. ZL
    Zhaosong Lu

    Simon Fraser University, Canada

    6 publications · 430 citations

    6

    h-index

  3. LX
    Lin Xiao

    Microsoft (United States), United States

    5 publications · 392 citations

    5

    h-index

  4. RT
    Roberto Tempo

    Politecnico di Torino, Italy

    5 publications · 328 citations

    5

    h-index

  5. ZQ
    Zheng Qu

    University of Edinburgh, United Kingdom

    5 publications · 202 citations

    5

    h-index

1–5 of 622

Venues

  1. arXiv (Cornell University)

    Repository · 36 publications · 2.1K citations

    18

    h-index

  2. SIAM Journal on Optimization

    10 publications · 884 citations

    10

    h-index

  3. IEEE Transactions on Automatic Control

    9 publications · 487 citations

    9

    h-index

  4. Mathematical Programming

    8 publications · 558 citations

    8

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 215 citations

    4

    h-index

1–5