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We present a scalable post-processing algorithm for debiasing trained models, including deep neural networks (DNNs), which we prove to be near-optimal by bounding its excess Bayes risk.
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Deep learning face attributes in the wild
Z. Liu, P. Luo, X. Wang, and X. Tang · 2015
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Man is to computer programmer as woman is to homemaker? debiasing word embeddings
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A confidence-based approach for balancing fairness and accuracy
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The promise and perils of algorithmic lenders’ use of big data
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Measuring and mitigating unintended bias in text classification
L. Dixon, J. Li, J. Sorensen, N. Thain, and L. Vasserman · 2018
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Beyond distributive fairness in algorithmic decision making: Feature selection for procedurally fair learning
N. Grgić-Hlača, M. B. Zafar, K. P. Gummadi, and A. Weller · 2018
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Learning adversarially fair and transferable representations
D. Madras, E. Creager, T. Pitassi, and R. Zemel · 2018
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The cost of fairness in binary classification
A. K. Menon and R. C. Williamson · 2018
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Mitigating unwanted biases with adversarial learning
B. H. Zhang, B. Lemoine, and M. Mitchell · 2018
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Inherent trade-offs in the fair determination of risk scores
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Optimized pre-processing for discrimination prevention
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Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
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Learning transferable architectures for scalable image recognition
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Classification with fairness constraints: A meta-algorithm with provable guarantees
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Does object recognition work for everyone?
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On the fairness of disentangled representations
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A survey on bias and fairness in machine learning
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Dissecting racial bias in an algorithm used to manage the health of populations
Z. Obermeyer, B. Powers, C. Vogeli, and S. Mullainathan · 2019
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Fairness and abstraction in sociotechnical systems
A. D. Selbst, D. Boyd, S. A. Friedler, S. Venkatasubramanian, and J. Vertesi · 2019
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Optimized score transformation for fair classification
D. Wei, K. N. Ramamurthy, and F. d. P. Calmon · 2019
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Fairness Constraints: A Flexible Approach for Fair Classification
M. B. Zafar, I. Valera, M. Gomez-Rodriguez, and K. P. Gummadi · 2019
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fairlearn 0.4.6
M. Dudik, R. Edgar, B. Horn, and R. Lutz · 2020
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Big transfer (BiT): General visual representation learning
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On robustness and transferability of convolutional neural networks
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