A fair pricing model via adversarial learning

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.

A fair pricing model via adversarial learning


OpenEdition suggests that you cite this post as follows:
Arthur Charpentier (June 29, 2022). A fair pricing model via adversarial learning. Freakonometrics. Retrieved July 18, 2024 from https://doi.org/10.58079/ovjo


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