Enhancing Fairness in Classification Tasks with Multiple Variables: A Data- and Model-Agnostic Approach

Giordano d'Aloisio, Giovanni Stilo, Antinisca Di Marco, Andrea D'Angelo. Enhancing Fairness in Classification Tasks with Multiple Variables: A Data- and Model-Agnostic Approach. In Ludovico Boratto, Stefano Faralli 0001, Mirko Marras, Giovanni Stilo, editors, Advances in Bias and Fairness in Information Retrieval - Third International Workshop, BIAS 2022, Stavanger, Norway, April 10, 2022, Revised Selected Papers. Volume 1610 of Communications in Computer and Information Science, pages 117-129, Springer, 2022. [doi]

@inproceedings{dAloisioSMD22,
  title = {Enhancing Fairness in Classification Tasks with Multiple Variables: A Data- and Model-Agnostic Approach},
  author = {Giordano d'Aloisio and Giovanni Stilo and Antinisca Di Marco and Andrea D'Angelo},
  year = {2022},
  doi = {10.1007/978-3-031-09316-6_11},
  url = {https://doi.org/10.1007/978-3-031-09316-6_11},
  researchr = {https://researchr.org/publication/dAloisioSMD22},
  cites = {0},
  citedby = {0},
  pages = {117-129},
  booktitle = {Advances in Bias and Fairness in Information Retrieval - Third International Workshop, BIAS 2022, Stavanger, Norway, April 10, 2022, Revised Selected Papers},
  editor = {Ludovico Boratto and Stefano Faralli 0001 and Mirko Marras and Giovanni Stilo},
  volume = {1610},
  series = {Communications in Computer and Information Science},
  publisher = {Springer},
  isbn = {978-3-031-09316-6},
}