Concepedia

Fairness Under Distribution Shift

Fairness Under Distribution Shift is a framework in algorithmic fairness that ensures equitable model performance across varying data distributions by maintaining fairness constraints despite shifts in the underlying input distribution from training to deployment.

6

Publications

192

Citations

37

Authors

5

Institutions

Publications per year

2017–2026

6

Parents

Publications

6

Environment Inference for Invariant Learning

Elliot Creager, Joern-Henrik Jacobsen, Richard S. Zemel · International Conference on Machine Learning · 2021 · 51 citations

, , +14

Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision

Priya Goyal, Quentin Duval, Isaac Seessel et al. · arXiv (Cornell University) · 2022 · 48 citations · Full text

, , +16

Robust Fairness Under Covariate Shift

Ashkan Rezaei, Anqi Liu, Omid Memarrast et al. · 2021 · 41 citations

, , +14

Diagnosing failures of fairness transfer across distribution shift in real-world medical settings

Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo et al. · arXiv (Cornell University) · 2022 · 32 citations · Full text

, , +15

Fairness Feedback Loops: Training on Synthetic Data Amplifies Bias

Sierra Wyllie, Ilia Shumailov, Nicolas Papernot · 2024 · 18 citations · Full text

, , +16

1–5 of 6

Authors

37

  1. EC
    Elliot Creager

    University of Toronto, Canada

    2 publications · 61 citations

    2

    h-index

  2. RS
    Richard S. Zemel

    University of Toronto, Canada

    2 publications · 61 citations

    2

    h-index

  3. AL
    Anqi Liu

    University of Illinois Chicago, United States

    1 publications · 41 citations

    1

    h-index

  4. MC
    Mathilde Caron

    Meta (Israel), Israel

    1 publications · 48 citations

    1

    h-index

  5. ES
    Eva Schnider

    1 publications · 32 citations

    1

    h-index

1–5 of 37

Institutions

5

  1. Vector Institute

    Toronto, Canada

    2 h-index

    2 publications

    61 citations

  2. Apple (Germany)

    Munich, Germany

    2 h-index

    2 publications

    61 citations

  3. University of Toronto

    Toronto, Canada

    2 h-index

    2 publications

    61 citations

  4. California Institute of Technology

    Pasadena, United States

    1 h-index

    1 publications

    41 citations

  5. University of Illinois Chicago

    Chicago, United States

    1 h-index

    3 publications

    123 citations

  6. University of Oxford

    Oxford, United Kingdom

    1 publications

    18 citations

1–6 of 5

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 100 citations

    4

    h-index

  2. International Conference on Machine Learning

    Conference · 1 publications · 51 citations

    1

    h-index

1–2