Validation Overfitting

Validation Overfitting is a form of overfitting in machine learning whereby a model is excessively tuned to the validation set during hyperparameter optimization or model selection, resulting in poor generalization to unseen test data despite favorable validation performance.

3

Publications

172

Citations

16

Authors

5

Institutions

Publications per year

2017–2026

2

Authors

16

  1. TW
    Tony Wong

    École de Technologie Supérieure, Canada

    1 publications · 16 citations

    1

    h-index

  2. NJ
    Naman Jain

    Indian Institute of Technology Bombay, India

    1 publications · 25 citations

    1

    h-index

  3. AS
    Armando Solar-Lezama

    Massachusetts Institute of Technology, United States

    1 publications · 25 citations

    1

    h-index

  4. LC
    Liushan Chen

    Hong Kong Polytechnic University, Hong Kong SAR China

    1 publications · 131 citations

    1

    h-index

  5. KS
    Koushik Sen

    University of California, Berkeley, United States

    1 publications · 25 citations

    1

    h-index

1–5 of 16

Venues

  1. 1

    h-index

  2. arXiv (Cornell University)

    Repository · 1 publications · 25 citations

    1

    h-index

1–2