Concepedia

Fair Representation Learning

Fair Representation Learning is a machine learning framework that belongs to the class of fairness-preserving methods by transforming原始输入数据 into a latent representation space wherein sensitive attributes are disentangled from predictive features to ensure equitable model outcomes.

163

Publications

9.6K

Citations

588

Authors

219

Institutions

Publications per year

2017–2026

157

Parents

Publications

163

Learning Fair Representations

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

, , +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

FairGAN: Fairness-aware Generative Adversarial Networks

Depeng Xu, Shuhan Yuan, Lu Zhang et al. · 2018 · 344 citations

, , +11

Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

Alex Beutel, Jilin Chen, Zhe Zhao · arXiv (Cornell University) · 2017 · 298 citations · Full text

, , +16

The Variational Fair Autoencoder

Christos Louizos, Kevin Swersky, Yujia Li et al. · Data Archiving and Networked Services (DANS) · 2016 · 271 citations · Full text

, , +12

1–5 of 163

Authors

588

  1. EC
    Elliot Creager

    University of Toronto, Canada

    4 publications · 379 citations

    4

    h-index

  2. KP
    Krishna P. Gummadi

    Max Planck Institute for Software Systems, Germany

    4 publications · 180 citations

    4

    h-index

  3. HZ
    Han Zhao

    Carnegie Mellon University, United States

    4 publications · 143 citations

    4

    h-index

  4. AG
    Aram Galstyan

    University of Southern California, United States

    4 publications · 231 citations

    4

    h-index

  5. NK
    Niki Kilbertus

    Max Planck Institute for Intelligent Systems, Germany

    4 publications · 149 citations

    4

    h-index

1–5 of 588

Institutions

219

  1. University of Toronto

    Toronto, Canada

    9 h-index

    27 publications

    7.1K citations

  2. Stanford University

    Stanford, United States

    7 h-index

    23 publications

    1.4K citations

  3. Carnegie Mellon University

    Pittsburgh, United States

    5 h-index

    8 publications

    454 citations

  4. University of California, Irvine

    Irvine, United States

    4 h-index

    5 publications

    528 citations

  5. Michigan State University

    East Lansing, United States

    4 h-index

    13 publications

    360 citations

  6. Google (United States)

    Mountain View, United States

    4 h-index

    17 publications

    478 citations

  7. National University of Singapore

    Singapore, Singapore

    4 h-index

    10 publications

    438 citations

  8. Max Planck Society

    Munich, Germany

    4 h-index

    6 publications

    205 citations

1–8 of 219

Venues

  1. arXiv (Cornell University)

    Repository · 51 publications · 2.7K citations

    26

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 7 publications · 216 citations

    7

    h-index

  3. Neural Information Processing Systems

    Conference · 5 publications · 219 citations

    5

    h-index

  4. International Conference on Machine Learning

    Conference · 5 publications · 283 citations

    5

    h-index

  5. 3

    h-index

1–5