Supervised Learning

Supervised Learning is a machine learning and statistical learning paradigm in which a model is trained on labeled input–output pairs to learn a mapping from inputs to outputs that generalizes to unseen data.

10.1K

Publications

1.1M

Citations

25.7K

Authors

4K

Institutions

Publications per year

2017–2026

5.9K

Authors

25.7K

  1. FN
    Feiping Nie

    Northwestern Polytechnical University, China

    44 publications · 2.5K citations

    33

    h-index

  2. ZZ
    Zhi‐Hua Zhou

    Nanjing University, China

    52 publications · 8K citations

    32

    h-index

  3. MS
    Masashi Sugiyama

    Tokyo Institute of Technology, Japan

    56 publications · 3.2K citations

    28

    h-index

  4. DT
    Dacheng Tao

    The University of Sydney, Australia

    43 publications · 4.2K citations

    28

    h-index

  5. MZ
    Min-Ling Zhang

    Southeast University, China

    27 publications · 5.5K citations

    23

    h-index

1–5 of 25.7K

Venues

  1. arXiv (Cornell University)

    Repository · 1K publications · 168.2K citations

    123

    h-index

  2. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 151 publications · 32.7K citations

    76

    h-index

  3. 52

    h-index

  4. Neurocomputing

    201 publications · 10.7K citations

    51

    h-index

  5. IEEE Transactions on Neural Networks

    88 publications · 22K citations

    51

    h-index

1–5