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.