no code implementations • 13 Dec 2023 • Evdoxia Taka, Yuri Nakao, Ryosuke Sonoda, Takuya Yokota, Lin Luo, Simone Stumpf
Fairness in AI is a growing concern for high-stakes decision making.
no code implementations • 23 May 2023 • Ryosuke Sonoda
Class imbalance and group (e. g., race, gender, and age) imbalance are acknowledged as two reasons in data that hinder the trade-off between fairness and utility of machine learning classifiers.
no code implementations • 29 Oct 2021 • Ryosuke Sonoda
As far as the fairness measurements in ranking are represented as a linear constraint of the ranking models, we proved that the minimization of loss function subject to the constraints is reduced to the closed solution of the minimization problem augmented by weights to training data.