Active Learning

Active Learning is a machine learning and statistical learning paradigm in which a learner adaptively selects informative unlabeled instances and queries an oracle for their labels so as to achieve target performance with a minimal number of labeled examples.

3.5K

Publications

234.6K

Citations

9K

Authors

2K

Institutions

Publications per year

2017–2026

1.7K

Authors

9K

  1. SH
    Sheng-Jun Huang

    Nanjing University of Aeronautics and Astronautics, China

    21 publications · 1.4K citations

    18

    h-index

  2. LB
    Lorenzo Bruzzone

    University of Trento, Italy

    18 publications · 1.6K citations

    17

    h-index

  3. SC
    Steven C. H. Hoi

    Nanyang Technological University, Singapore

    19 publications · 1.7K citations

    16

    h-index

  4. KG
    Kristen Grauman

    The University of Texas at Austin, United States

    16 publications · 1.6K citations

    16

    h-index

  5. JL
    Jun Li

    Sun Yat-sen University, China

    17 publications · 2.3K citations

    15

    h-index

1–5 of 9K

Venues

  1. arXiv (Cornell University)

    Repository · 218 publications · 9.5K citations

    44

    h-index

  2. 40

    h-index

  3. Reliability Engineering & System Safety

    33 publications · 1.7K citations

    27

    h-index

  4. 26

    h-index

  5. Neurocomputing

    50 publications · 2K citations

    26

    h-index

1–5