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Consequential decisions are increasingly informed by sophisticated data-driven predictive models.
Stochastic estimation of the maximum of a regression function
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Estimation of non-normalized statistical models by score matching
Hyvärinen, A · 2005
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Causal inference using potential outcomes
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Exploration scavenging
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Causality
Pearl, J · 2009
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Doubly Robust Policy Evaluation and Learning
Dudík, M., Langford, J., and Li, L · 2011
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Fairness through awareness
Dwork, C., Hardt, M., Pitassi, T., Reingold, O., and Zemel, R · 2012
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Counterfactual reasoning and learning systems: The example of computational advertising
Bottou, L., Peters, J., nonero Candela, J. Q., Charles, D. X., Chickering, D. M., Portugaly, E., Ray, D., Simard, P., and Snelson, E · 2013
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Taming the monster: A fast and simple algorithm for contextual bandits
Agarwal, A., Hsu, D., Kale, S., Langford, J., Li, L., and Schapire, R · 2014
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Deterministic policy gradient algorithms
Silver, D., Lever, G., Heess, N., Degris, T., Wierstra, D., and Riedmiller, M · 2014
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Certifying and removing disparate impact
Feldman, M., Friedler, S. A., Moeller, J., Scheidegger, C., and Venkatasubramanian, S · 2015
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Machine bias: There is software used across the country to predict future criminals. and it is biased against blacks
Angwin, J., Larson, J., Mattu, S., and Kirchner, L · 2016
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Equality of opportunity in supervised learning
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Fairness in learning: Classic and contextual bandits
Joseph, M., Kearns, M., Morgenstern, J. H., and Roth, A · 2016
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Athey, S. and Wager, S · 2017
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Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Chouldechova, A · 2017
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Algorithmic decision making and the cost of fairness
Corbett-Davies, S., Pierson, E., Feller, A., Goel, S., and Huq, A · 2017
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Fairness in reinforcement learning
Jabbari, S., Joseph, M., Kearns, M., Morgenstern, J., and Roth, A · 2017
Algorithmic decision making in the presence of unmeasured confounding
Jung, J., Shroff, R., Feller, A., and Goel, S · 2018
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Balanced policy evaluation and learning
Kallus, N · 2018
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Residual unfairness in fair machine learning from prejudiced data
Kallus, N. and Zhou, A · 2018
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Algorithmic fairness
Kleinberg, J., Ludwig, J., Mullainathan, S., and Rambachan, A · 2018
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Delayed impact of fair machine learning
Liu, L. T., Dean, S., Rolf, E., Simchowitz, M., and Hardt, M · 2018
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Prediction-based decisions and fairness: A catalogue of choices, assumptions, and definitions
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Inherent Trade-Offs in the Fair Determination of Risk Scores
Kleinberg, J., Mullainathan, S., and Raghavan, M · 2017
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Learning Cost-Effective and Interpretable Treatment Regimes
Lakkaraju, H. and Rudin, C · 2017
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The selective labels problem: Evaluating algorithmic predictions in the presence of unobservables
Lakkaraju, H., Kleinberg, J., Leskovec, J., Ludwig, J., and Mullainathan, S · 2017
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Learning non-discriminatory predictors
Woodworth, B., Gunasekar, S., Ohannessian, M. I., and Srebro, N · 2017
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Decision making with limited feedback: Error bounds for recidivism prediction and predictive policing
Ensign, D., Friedler, S. A., Neville, S., Scheidegger, C., and Venkatasubramanian, S · 2018
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Online learning with an unknown fairness metric
Gillen, S., Jung, C., Kearns, M., and Roth, A · 2018
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Mitchell, S., Potash, E., and Barocas, S · 2018
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Enhancing the accuracy and fairness of human decision making
Valera, I., Singla, A., and Gomez-Rodriguez, M · 2018
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Fairness and Machine Learning
Barocas, S., Hardt, M., and Narayanan, A · 2019
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Bayesian fairness
Dimitrakakis, C., Liu, Y., Parkes, D., and Radanovic, G · 2019
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Improving fairness in machine learning systems: What do industry practitioners need?
Holstein, K., Wortman Vaughan, J., Daumé, H., Dudik, M., and Wallach, H · 2019
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Objecting to experiments that compare two unobjectionable policies or treatments
Meyer, M. N., Heck, P. R., Holtzman, G. S., Anderson, S. M., Cai, W., Watts, D. J., and Chabris, C. F · 2019
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From fair decision making to social equality
Mouzannar, H., Ohannessian, M. I., and Srebro, N · 2019
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Performative prediction
Perdomo, J. C., Zrnic, T., Mendler-Dünner, C., and Hardt, M · 2020
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An economic approach to regulating algorithms
Rambachan, A., Kleinberg, J., Mullainathan, S., and Ludwig, J · 2020
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