Confidence Learning

Confidence Learning is a machine learning framework that systematically adjusts model confidence estimates to align with empirical accuracy through iterative calibration and feedback.

54

Publications

3.1K

Citations

204

Authors

88

Institutions

Publications per year

2017–2026

37

Authors

204

  1. MD
    Mark Dredze

    Johns Hopkins University, United States

    4 publications · 627 citations

    4

    h-index

  2. KC
    Koby Crammer

    Technion – Israel Institute of Technology, Israel

    4 publications · 627 citations

    4

    h-index

  3. FP
    Fernando Pereira

    Instituto de Telecomunicações, Portugal

    3 publications · 547 citations

    3

    h-index

  4. CC
    Chu‐Song Chen

    Institute of Information Science, Academia Sinica, Taiwan

    2 publications · 155 citations

    2

    h-index

  5. MD
    Mostafa Dehghani

    Google (United States), United States

    2 publications · 67 citations

    2

    h-index

1–5 of 204

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 248 citations

    7

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 92 citations

    3

    h-index

  3. IEEE Transactions on Medical Imaging

    2 publications · 119 citations

    2

    h-index

  4. 2009 IEEE Conference on Computer Vision and Pattern Recognition

    Conference · 2 publications · 155 citations

    2

    h-index

  5. Journal of Intelligent Information Systems

    1 publications · 18 citations

    1

    h-index

1–5