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A Distributionally Robust Approach to Fair Classification
16 references·0 citing·27 second hop
A Distributionally Robust Approach to Fair Classification (2020)A Distributionally Robust Approach to Fai…A Survey on Bias and Fairness in Machine Learning (2021)A Survey on Bias and Fairness…Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)Fairness in Criminal Justice …Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…Algorithmic Decision Making and the Cost of Fairness (2017)Algorithmic Decision Making a…Inherent Trade-Offs in the Fair Determination of Risk Scores (2016)Inherent Trade-Offs in the Fa…Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Data-Driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations (2015)Data-Driven Distributionally …Certifying and Removing Disparate Impact (2015)Certifying and Removing Dispa…Distributionally Robust Convex Optimization (2014)Distributionally Robust Conve…Big Data's Disparate Impact (2014)Big Data's Disparate ImpactLearning Fair Representations (2013)Learning Fair RepresentationsFairness through awareness (2012)Fairness through awarenessData preprocessing techniques for classification without discrimination (2011)Data preprocessing techniques…Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems (2010)Distributionally Robust Optim…Studies in Mathematical Theory of Inventory and Production (1959)Robust Convex Optimization (1998)Optimization of conditional value-at-risk (2000)Recent advances in robust optimization: An overview (2013)Uniform Guidelines on Employee Selection Procedures (2007)European Union Regulations on Algorithmic Decision Making and a “Right to Explanation” (2017)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Addressing bias in big data and AI for health care: A call for open science (2021)The Price of Robustness (2004)Robust Optimization (2009)Data-driven robust optimization (2017)Distributionally Robust Stochastic Optimization with Wasserstein Distance (2022)Frameworks and Results in Distributionally Robust Optimization (2022)Semantics derived automatically from language corpora contain human-like biases (2017)Algorithmic Bias in Education (2021)Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Dissecting racial bias in an algorithm used to manage the health of populations (2019)Fairness and Abstraction in Sociotechnical Systems (2019)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)The ethics of algorithms: Mapping the debate (2016)
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References

  • 2021A Survey on Bias and Fairness in Machine Learning5,798 cited
  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 2012Fairness through awareness3,501 cited
  • 2014Big Data's Disparate Impact3,046 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,157 cited
  • 2010Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems1,910 cited
  • 2015Data-Driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations1,869 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2011Data preprocessing techniques for classification without discrimination1,304 cited
  • 2017Algorithmic Decision Making and the Cost of Fairness1,149 cited
  • 2013Learning Fair Representations1,126 cited
  • 2018Fairness in Criminal Justice Risk Assessments: The State of the Art986 cited
  • 2014Distributionally Robust Convex Optimization

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952 cited
  • 2016Inherent Trade-Offs in the Fair Determination of Risk Scores942 cited
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