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GroupMixNorm Layer for Learning Fair Models
Analysis on benchmark tabular and image datasets demonstrates the efficacy of the proposed method in achieving state-of-the-art performance.
FairGen: Fair Synthetic Data Generation
Existing work focusing on generating fair data either works for a certain GAN architecture or is very difficult to tune across the GANs.
Simultaneous Improvement of ML Model Fairness and Performance by Identifying Bias in Data
Machine learning models built on datasets containing discriminative instances attributed to various underlying factors result in biased and unfair outcomes.
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