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In classification models fairness can be ensured by solving a constrained optimization problem.
The well-calibrated bayesian
A. P. Dawid · 1982
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Rademacher and gaussian complexities: Risk bounds and structural results
Peter L Bartlett and Shahar Mendelson · 2002
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M. talagrand probability in banach spaces first reprint, 2002
M Ledoux · 2002
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Classifying without discriminating
F. Kamiran and T. Calders · 2009
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Three naive bayes approaches for discrimination-free classification
Toon Calders and Sicco Verwer · 2010
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Classification with no discrimination by preferential sampling
F. Kamiran and T.G.K. Calders · 2010
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Fairness-aware learning through regularization approach
T. Kamishima, S. Akaho, and J. Sakuma · 2011
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Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel · 2012
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Learning fair representations
Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork · 2013
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Rademacher Complexities
Shai Shalev-Shwartz and Shai Ben-David · 2014
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Fairness Constraints: Mechanisms for Fair Classification
M. Bilal Zafar, I. Valera, M. Gomez Rodriguez, and K. P. Gummadi · 2015
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Certifying and removing disparate impact
Michael Feldman, Sorelle A. Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian · 2015
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The variational fair autoencoder
Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, and Richard S. Zemel · 2015
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Big data’s disparate impact
Solon Barocas and Andrew D Selbst · 2016
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Data decisions and theoretical implications when adversarially learning fair representations
Alex Beutel, Jilin Chen, Zhe Zhao, and Ed Huai hsin Chi · 2017
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Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova · 2017
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Optimal auctions through deep learning
Paul Dütting, Zhe Feng, Harikrishna Narasimhan, David C Parkes, and Sai Srivatsa Ravindranath · 2017
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On fairness and calibration
Geoff Pleiss, Manish Raghavan, Felix Wu, Jon Kleinberg, and Kilian Q Weinberger · 2017
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A reductions approach to fair classification
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudik, John Langford, and Hanna Wallach · 2018
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Elad ET Eban, Mariano Schain, Alan Mackey, Ariel Gordon, Rif A Saurous, and Gal Elidan · 2016
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Censoring representations with an adversary
Harrison Edwards and Amos Storkey · 2016
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nathan Srebro · 2016
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Learning fair classifiers: A regularization-inspired approach
Yahav Bechavod and Katrina Ligett · 2017
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Fairness in criminal justice risk assessments: The state of the art
Richard Berk, Hoda Heidari, Shahin Jabbari, Michael Kearns, and Aaron Roth
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Learning adversarially fair and transferable representations
David Madras, Elliot Creager, Toniann Pitassi, and Richard S. Zemel · 2018
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Learning with complex loss functions and constraints
Harikrishna Narasimhan · 2018
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Fairness-aware classification: Criterion, convexity, and bounds
Yongkai Wu, Lu Zhang, and Xintao Wu · 2018
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Mitigating unwanted biases with adversarial learning
Brian Hu Zhang, Blake Lemoine, and Margaret Mitchell · 2018
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