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Many instances of algorithmic bias are caused by subpopulation shifts.
Linear Operators
Nelson Dunford, Jacob T. Schwartz, William G. Bade, and Robert G. Bartle · 1958
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Perturbation Analysis of Optimization Problems
Joseph Frédéric Bonnans and Alexander Shapiro · 2000
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UCI machine learning repository
K. Bache and M. Lichman · 2013
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Machine Bias
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner · 2016
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Equality of Opportunity in Supervised Learning
Moritz Hardt, Eric Price, and Nathan Srebro · 2016
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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 · 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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On conditional parity as a notion of non-discrimination in machine learning
Ya’acov Ritov, Yuekai Sun, and Ruofei Zhao · 2017
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Shreya Shankar, Yoni Halpern, Eric Breck, James Atwood, Jimbo Wilson, and D. Sculley · 2017
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A Reductions Approach to Fair Classification
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, and Hanna Wallach · 2018
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Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
Joy Buolamwini and Timnit Gebru · 2018
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Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
Andrew Cotter, Maya Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Wang, Blake Woodworth, and Seungil You · 2018
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Empirical Risk Minimization Under Fairness Constraints
Michele Donini, Luca Oneto, Shai Ben-David, John S. Shawe-Taylor, and Massimiliano Pontil · 2018
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Selection Problems in the Presence of Implicit Bias
Jon Kleinberg and Manish Raghavan · 2018
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Dissecting racial bias in an algorithm used to manage the health of populations
Ziad Obermeyer, Brian Powers, Christine Vogeli, and Sendhil Mullainathan · 2019
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The Best Algorithms Still Struggle to Recognize Black Faces
Tom Simonite · 2019
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Predictive Inequity in Object Detection
Benjamin Wilson, Judy Hoffman, and Jamie Morgenstern · 2019
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Samuel Yeom and Michael Carl Tschantz · 2019
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Interventions for ranking in the presence of implicit bias
L. Elisa Celis, Anay Mehrotra, and Nisheeth K. Vishnoi · 2020
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Fair Regression: Quantitative Definitions and Reduction-based Algorithms
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Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?
Avrim Blum and Kevin Stangl · 2019
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Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals
Andrew Cotter, Heinrich Jiang, Maya Gupta, Serena Wang, Taman Narayan, Seungil You, and Karthik Sridharan · 2019
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An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, and Kush R. Varshney · 2019
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Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, and Percy Liang · 2020
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Towards fairer datasets: Filtering and balancing the distribution of the people subtree in the imagenet hierarchy
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Training individually fair ML models with sensitive subspace robustness
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{BREEDS}: Benchmarks for subpopulation shift
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