11 citations · 13 across the 4 of their papers we have counts for
4 papers
Direct and Indirect Discrimination in Generalized Linear Models
Bertille Tierny, Arthur Charpentier, François Hu
Generalized linear models are central to actuarial modelling of binary risk, claim frequency, utilization, and cost-related outcomes. Yet fairness diagnostics often rely on linear-…
Fairness Explainability using Optimal Transport with Applications in Image Classification
Philipp Ratz, François Hu, Arthur Charpentier
Ensuring trust and accountability in Artificial Intelligence systems demands explainability of its outcomes. Despite significant progress in Explainable AI, human biases still tain…
Fair Active Learning: Solving the Labeling Problem in Insurance
Romuald Elie, Caroline Hillairet, François Hu +1
This paper addresses significant obstacles that arise from the widespread use of machine learning models in the insurance industry, with a specific focus on promoting fairness. The…
Fairness guarantee in multi-class classification
Christophe Denis, Romuald Elie, Mohamed Hebiri +1
Algorithmic Fairness is an established area of machine learning, willing to reduce the influence of hidden bias in the data. Yet, despite its wide range of applications, very few w…