Nice review of our paper, with Vincent Grari, on montrealethics.ai.
Sacrificing predictive performance is often viewed as an unacceptable option in machine learning. However, we note that to satisfy a fairness objective, the predictive performance can be reduced too much, especially for generic fair algorithms. Therefore, we have developed a more suitable and practical framework by using autoencoders techniques.
OpenEdition suggests that you cite this post as follows:
Arthur Charpentier (June 29, 2022). A fair pricing model via adversarial learning. Freakonometrics. Retrieved September 14, 2026 from https://doi.org/10.58079/ovjo