Jourdan, F.; Kaninku, T.T.; Asher, N.; Loubes, J.-M.; Risser, L.
How Optimal Transport Can Tackle Gender Biases in Multi-Class Neural Network Classifiers for Job Recommendations. Algorithms 2023, 16, 174.
https://doi.org/10.3390/a16030174
AMA Style
Jourdan F, Kaninku TT, Asher N, Loubes J-M, Risser L.
How Optimal Transport Can Tackle Gender Biases in Multi-Class Neural Network Classifiers for Job Recommendations. Algorithms. 2023; 16(3):174.
https://doi.org/10.3390/a16030174
Chicago/Turabian Style
Jourdan, Fanny, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, and Laurent Risser.
2023. "How Optimal Transport Can Tackle Gender Biases in Multi-Class Neural Network Classifiers for Job Recommendations" Algorithms 16, no. 3: 174.
https://doi.org/10.3390/a16030174
APA Style
Jourdan, F., Kaninku, T. T., Asher, N., Loubes, J. -M., & Risser, L.
(2023). How Optimal Transport Can Tackle Gender Biases in Multi-Class Neural Network Classifiers for Job Recommendations. Algorithms, 16(3), 174.
https://doi.org/10.3390/a16030174