Classification Surrogates

Classification Surrogates is a type of surrogate model that, within the genus of classification models, differs by serving as an interpretable or computationally efficient approximation of a more complex classifier, designed to mimic its decision boundary while enabling analysis, validation, or deployment under resource constraints.

52

Publications

2.1K

Citations

177

Authors

106

Institutions

Publications per year

2017–2026

23

Authors

177

  1. HG
    Harish G. Ramaswamy

    Indian Institute of Science Bangalore, India

    4 publications · 72 citations

    4

    h-index

  2. SA
    Shivani Agarwal

    Indian Institute of Science Bangalore, India

    4 publications · 72 citations

    4

    h-index

  3. SG
    Sujit Gujar

    International Institute of Information Technology, Hyderabad, India

    2 publications · 56 citations

    2

    h-index

  4. LG
    Lihua Gao

    Central South University, China

    2 publications · 76 citations

    2

    h-index

  5. HH
    Hongyan Huang

    Beijing Shijitan Hospital, China

    2 publications · 76 citations

    2

    h-index

1–5 of 177

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 147 citations

    6

    h-index

  2. IEEE Transactions on Evolutionary Computation

    3 publications · 211 citations

    3

    h-index

  3. Frontiers in Oncology

    2 publications · 76 citations

    2

    h-index

  4. Journal of Vegetation Science

    JVS · 2 publications · 25 citations

    2

    h-index

  5. Biological Conservation

    2 publications · 229 citations

    2

    h-index

1–5