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Machine learning models are becoming pervasive in high-stakes applications.
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Fairness in criminal justice risk assessments: The state of the art
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Integrating Psychometrics and Computing Perspectives on Bias and Fairness in Affective Computing: A case study of automated video interviews
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Fairness in TabNet Model by Disentangled Representation for the Prediction of Hospital No-Show
Sabri Boughorbel, Fethi Jarray, and Abdou Kadri. 2021 · 2021
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FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders. In International Conference on Learning Representations
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Fairness via Representation Neutralization
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Maxmin-Fair Ranking: Individual Fairness under Group-Fairness Constraints. In ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
David Garcia-Soriano and Francesco Bonchi. 2021 · 2021
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Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder. In AAAI Conference on Artificial Intelligence
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Fairness-Aware Node Representation Learning
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A survey on bias and fairness in machine learning
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Learning Disentangled Representation for Fair Facial Attribute Classification via Fairness-aware Information Alignment. In AAAI Conference on Artificial Intelligence , Vol. 35. 2403–2411
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Directional bias amplification
Angelina Wang and Olga Russakovsky. 2021 · 2021
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