Preprocessing Debiasing

Preprocessing Debiasing is a methodological approach in machine learning that belongs to the class of bias mitigation techniques and is distinguished by its application prior to model training to modify input data or features in order to reduce or eliminate unfair representational biases with respect to protected attributes.

6

Publications

163

Citations

22

Authors

10

Institutions

Publications per year

2017–2026

4

Authors

22

  1. SM
    Sebastian M. Blanc

    Karlsruhe Institute of Technology, Germany

    1 publications · 24 citations

    1

    h-index

  2. LZ
    Lihua Zhang

    Dalian University of Technology, China

    1 publications · 25 citations

    1

    h-index

  3. TS
    Thomas Setzer

    Technical University of Munich, Germany

    1 publications · 24 citations

    1

    h-index

  4. ML
    Miloš Lompar

    University of Belgrade, Serbia

    1 publications · 42 citations

    1

    h-index

  5. DC
    Danne C. Elbers

    VA Boston Healthcare System, United States

    1 publications · 25 citations

    1

    h-index

1–5 of 22

Venues

  1. Atmosphere

    1 publications · 42 citations

    1

    h-index

  2. European Journal of Operational Research

    1 publications · 24 citations

    1

    h-index

  3. IEEE Access

    1 publications · 29 citations

    1

    h-index

  4. ACM Transactions on Computing for Healthcare

    1 publications · 25 citations

    1

    h-index

  5. International Journal of Climatology

    1 publications · 18 citations

    1

    h-index

1–5