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Prediction systems are successfully deployed in applications ranging from disease diagnosis, to predicting credit worthiness, to image recognition.
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Adam Tauman Kalai, Yishay Mansour, and Elad Verbin · 2008
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Regularity, boosting, and efficiently simulating every high-entropy distribution
Luca Trevisan, Madhur Tulsiani, and Salil Vadhan · 2009
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Vitaly Feldman · 2010
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Effective unconstrained face recognition by combining multiple descriptors and learned background statistics
Lior Wolf, Tal Hassner, and Yaniv Taigman · 2011
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Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard S. Zemel · 2012
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Boosting: Foundations and algorithms
Robert E Schapire and Yoav Freund · 2012
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Concentration inequalities: A nonasymptotic theory of independence
Stéphane Boucheron, Gábor Lugosi, and Pascal Massart · 2013
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Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork · 2013
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Convex optimization: Algorithms and complexity
Sébastien Bubeck et al · 2015
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The reusable holdout: Preserving validity in adaptive data analysis
Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Aaron Roth · 2015
Algorithmic decision making and the cost of fairness
Sam Corbett-Davies, Emma Pierson, Avi Feller, Sharad Goel, and Aziz Huq · 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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Decoupled classifiers for fair and efficient machine learning
Cynthia Dwork, Nicole Immorlica, Adam Tauman Kalai, and Max Leiserson · 2017
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Inherent trade-offs in the fair determination of risk scores
Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan · 2017
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Preventing fairness gerrymandering: Auditing and learning for subgroup fairness
Michael Kearns, Seth Neel, Aaron Roth, and Zhiwei Steven Wu · 2017
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Uk biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age
Cathie Sudlow, John Gallacher, Naomi Allen, Valerie Beral, Paul Burton, John Danesh, Paul Downey, Paul Elliott, Jane Green, Martin Landray, et al · 2015
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Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin · 2015
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Machine bias: There’s software used across the country to predict future criminals. and it’s biased against blacks
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner · 2016
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Fairer and more accurate, but for whom?
Alexandra Chouldechova and Max G’Sell · 2016
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nathan Srebro · 2016
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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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Inception-v4, inception-resnet and the impact of residual connections on learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi · 2017
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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
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Calibration for the (computationally-identifiable) masses
Úrsula Hébert-Johnson, Michael P. Kim, Omer Reingold, and Guy N. Rothblum · 2018
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Fairness without demographics in repeated loss minimization
Tatsunori B Hashimoto, Megha Srivastava, Hongseok Namkoong, and Percy Liang · 2018
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Fairness through computationally-bounded awareness
Michael P. Kim, Omer Reingold, and Guy N. Rothblum · 2018
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Detecting and correcting for label shift with black box predictors
Zachary C. Lipton, Yu-Xiang Wang, and Alexander J. Smola · 2018
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Probably approximately metric-fair learning
Guy N. Rothblum and Gal Yona · 2018
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