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Adaptive Boosting with Fairness-aware Reweighting Technique for Fair Classification
In order to achieve fair classification, a novel fair AdaBoost (FAB) approach is proposed that is an interpretable fairness-improving variant of AdaBoost.
Parallel Bayesian Optimization Using Satisficing Thompson Sampling for Time-Sensitive Black-Box Optimization
We shift the target from an optimal solution to a satisficing solution that is easier to learn.
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