Concepedia

Fairness-aware Learning

Fairness-Aware Learning is a machine learning paradigm that incorporates fairness considerations into the model training process to mitigate biases against sensitive attributes, distinguishing itself from standard learning approaches by explicitly balancing accuracy and equity in predictive outcomes.

288

Publications

18.5K

Citations

958

Authors

348

Institutions

Publications per year

2017–2026

282

Parents

Publications

288

Fairness and Abstraction in Sociotechnical Systems

Andrew D. Selbst, danah boyd, Sorelle A. Friedler et al. · 2019 · 1.3K citations · Full text

, , +14

Ensuring Fairness in Machine Learning to Advance Health Equity

Alvin Rajkomar, Michaela Hardt, Michael Howell et al. · Annals of Internal Medicine · 2018 · 1.2K citations · Full text

, , +17

Learning Fair Representations

Rich Zemel, Yu Wu, Kevin Swersky et al. · 2013 · 1K citations

, , +16

Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment

Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez et al. · arXiv (Cornell University) · 2016 · 591 citations · Full text

, , +16

A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data

Lu Lu · arXiv (Cornell University) · 2021 · 470 citations · Full text

, , +16

1–5 of 288

Authors

958

  1. KP
    Krishna P. Gummadi

    Max Planck Institute for Software Systems, Germany

    9 publications · 1.1K citations

    9

    h-index

  2. XW
    Xintao Wu

    University of Arkansas at Fayetteville, United States

    8 publications · 646 citations

    8

    h-index

  3. LZ
    Lu Zhang

    University of Arkansas at Fayetteville, United States

    7 publications · 626 citations

    7

    h-index

  4. EC
    Elliot Creager

    University of Toronto, Canada

    7 publications · 545 citations

    7

    h-index

  5. AW
    Adrian Weller

    University of Cambridge, United Kingdom

    7 publications · 316 citations

    7

    h-index

1–5 of 958

Institutions

348

  1. Stanford University

    Stanford, United States

    11 h-index

    46 publications

    3K citations

  2. University of Toronto

    Toronto, Canada

    10 h-index

    27 publications

    6.2K citations

  3. Google (United States)

    Mountain View, United States

    10 h-index

    30 publications

    5.7K citations

  4. Max Planck Society

    Munich, Germany

    9 h-index

    20 publications

    1.6K citations

  5. Max Planck Institute for Software Systems

    Saarbrücken, Germany

    8 h-index

    20 publications

    3.5K citations

  6. Carnegie Mellon University

    Pittsburgh, United States

    8 h-index

    14 publications

    764 citations

  7. University College London

    London, United Kingdom

    7 h-index

    7 publications

    719 citations

  8. Massachusetts Institute of Technology

    Cambridge, United States

    6 h-index

    17 publications

    609 citations

1–8 of 348

Venues

  1. arXiv (Cornell University)

    Repository · 79 publications · 3.8K citations

    29

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 11 publications · 526 citations

    10

    h-index

  3. 5

    h-index

  4. International Conference on Machine Learning

    Conference · 4 publications · 277 citations

    4

    h-index

  5. Neural Information Processing Systems

    Conference · 4 publications · 116 citations

    4

    h-index

1–5