Adjusting CNN emotion-class probabilities by subtracting fitted gender coefficients, one class at a time, reduced male/female true-positive-rate gaps on a FairFace/DeepFace test set without lowering accuracy.
Data augmentation for discrimination prevention and bias disambiguation,
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Mitigating Algorithmic Bias in Multiclass CNN Classifications Using Causal Modeling
Adjusting CNN emotion-class probabilities by subtracting fitted gender coefficients, one class at a time, reduced male/female true-positive-rate gaps on a FairFace/DeepFace test set without lowering accuracy.