3 papers - avg viability 4.3
A post-processing framework that enhances fairness in machine learning predictions without altering model internals, applicable across diverse tasks and fairness definitions.
A novel regression fairness method that enforces distributional parity at specific quantiles or thresholds, offering a tunable trade-off between fairness and accuracy.
A generalized algorithm to enhance fairness in multi-class classification tasks by balancing prediction accuracy with multiple fairness constraints.