Surrogate-assisted Gradient Estimation

Surrogate-Assisted Gradient Estimation is a computational technique within surrogate-based optimization that approximates gradient information of an expensive black-box objective function by leveraging a surrogate model to enable gradient-based optimization methods.

19

Publications

1.2K

Citations

78

Authors

32

Institutions

Publications per year

2017–2026

17

Authors

78

  1. LG
    Liang Gao

    Huazhong University of Science and Technology, China

    3 publications · 185 citations

    3

    h-index

  2. XC
    Xiwen Cai

    Huazhong University of Science and Technology, China

    2 publications · 118 citations

    2

    h-index

  3. KZ
    Kai Zhao

    Chongqing University, China

    1 publications · 30 citations

    1

    h-index

  4. LR
    Larry Rudolph

    Massachusetts Institute of Technology, United States

    1 publications · 27 citations

    1

    h-index

  5. PW
    Peng Wang

    Northwestern Polytechnical University, China

    1 publications · 55 citations

    1

    h-index

1–5 of 78

Venues

  1. Applied Soft Computing

    4 publications · 205 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 63 citations

    3

    h-index

  3. Swarm and Evolutionary Computation

    2 publications · 65 citations

    2

    h-index

  4. Information Sciences

    2 publications · 208 citations

    2

    h-index

  5. Structural and Multidisciplinary Optimization

    2 publications · 256 citations

    2

    h-index

1–5