An Empirical Study of Rich Subgroup Fairness for Machine Learning. Kearns, M. J., Neel, S., Roth, A., & Wu, Z. S. In danah boyd & Morgenstern, J. H., editors, Proceedings of the Conference on Fairness, Accountability, and Transparency, FAT* 2019, Atlanta, GA, USA, January 29-31, 2019, pages 100–109, 2019. ACM.
An Empirical Study of Rich Subgroup Fairness for Machine Learning [link]Paper  doi  bibtex   1 download  
@inproceedings{DBLP:conf/fat/KearnsNRW19,
  author       = {Michael J. Kearns and
                  Seth Neel and
                  Aaron Roth and
                  Zhiwei Steven Wu},
  editor       = {danah boyd and
                  Jamie H. Morgenstern},
  title        = {An Empirical Study of Rich Subgroup Fairness for Machine Learning},
  booktitle    = {Proceedings of the Conference on Fairness, Accountability, and Transparency,
                  FAT* 2019, Atlanta, GA, USA, January 29-31, 2019},
  pages        = {100--109},
  publisher    = {{ACM}},
  year         = {2019},
  url          = {https://doi.org/10.1145/3287560.3287592},
  doi          = {10.1145/3287560.3287592},
  timestamp    = {Sat, 30 Sep 2023 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/fat/KearnsNRW19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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