Bootstrapped Loss Estimation

Bootstrapped Loss Estimation is a statistical method for quantifying uncertainty in loss predictions by repeatedly resampling observed loss data with replacement to generate empirical distributions of estimated loss parameters.

5

Publications

391

Citations

13

Authors

6

Institutions

Publications per year

2017–2026

1

Authors

13

  1. DO
    Diego Ortego

    Dublin City University, Ireland

    1 publications · 198 citations

    1

    h-index

  2. RM
    Ruud M. Bolle

    IBM Research - Thomas J. Watson Research Center, United States

    1 publications · 86 citations

    1

    h-index

  3. RC
    Ricardo Cao

    Universidade da Coruña, Spain

    1 publications · 27 citations

    1

    h-index

  4. PA
    Paul Albert

    Concordia University, Canada

    1 publications · 198 citations

    1

    h-index

  5. KM
    Kevin McGuinness

    Dublin City University, Ireland

    1 publications · 198 citations

    1

    h-index

1–5 of 13

Venues

  1. Computer Vision and Image Understanding

    CVIU · 1 publications · 86 citations

    1

    h-index

  2. Warwick Research Archive Portal (University of Warwick)

    Repository · 1 publications · 33 citations

    1

    h-index

  3. The Annals of Statistics

    1 publications · 47 citations

    1

    h-index

  4. Test

    1 publications · 27 citations

    1

    h-index

  5. arXiv (Cornell University)

    Repository · 1 publications · 198 citations

    1

    h-index

1–5