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Learning Fair and Transferable Representations with Theoretical Guarantees
16 references·3 citing·30 second hop
Learning Fair and Transferable Representations with Theoretical Guarantees (2020)Learning Fair and Transferable Representa…Path-Specific Counterfactual Fairness (2019)Path-Specific Counterfactual …Actionable Auditing (2019)Actionable AuditingLearning Adversarially Fair and Transferable Representations (2018)Learning Adversarially Fair a…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…Fairness definitions explained (2018)Fairness definitions explainedA Reductions Approach to Fair Classification (2018)A Reductions Approach to Fair…Optimized Pre-Processing for Discrimination Prevention (2017)Optimized Pre-Processing for …On Fairness and Calibration (2017)On Fairness and CalibrationFairness Beyond Disparate Treatment & Disparate Impact (2017)Fairness Beyond Disparate Tre…Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations (2017)Data Decisions and Theoretica…Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment (2016)Fairness Beyond Disparate Tre…Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Certifying and Removing Disparate Impact (2015)Certifying and Removing Dispa…Big Data's Disparate Impact (2014)Big Data's Disparate ImpactLearning Fair Representations (2013)Learning Fair RepresentationsFairness-Aware Classifier with Prejudice Remover Regularizer (2012)Fairness-Aware Classifier wit…Fix Fairness, Don’t Ruin Accuracy: Performance Aware Fairness Repair using AutoML (2023)Fix Fairness, Don’t Ruin Accu…Image fairness in deep learning: problems, models, and challenges (2022)Image fairness in deep learni…FairNN - Conjoint Learning of Fair Representations for Fair Decisions (2020)FairNN - Conjoint Learning of…Discrimination-aware data mining (2008)Three naive Bayes approaches for discrimination-free classification (2010)Fairness through awareness (2012)Fair, Transparent, and Accountable Algorithmic Decision-making Processes (2017)Trustworthy Artificial Intelligence: A Review (2022)Fairness in Machine Learning: A Survey (2023)Uniform Guidelines on Employee Selection Procedures (2007)European Union Regulations on Algorithmic Decision Making and a “Right to Explanation” (2017)Semantics derived automatically from language corpora contain human-like biases (2017)A Survey on Bias and Fairness in Machine Learning (2021)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fairness in Machine Learning: Lessons from Political Philosophy (2017)Fairness of Exposure in Rankings (2018)Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse (2019)Accountability in algorithmic decision making (2016)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Legal and human rights issues of AI: Gaps, challenges and vulnerabilities (2020)Roles for computing in social change (2020)Ethics of AI-Enabled Recruiting and Selection: A Review and Research Agenda (2022)Algorithmic Decision Making and the Cost of Fairness (2017)Counterfactual Fairness (2017)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)Bias in data‐driven artificial intelligence systems—An introductory survey (2020)Algorithmic Bias in Education (2021)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)The ethics of algorithms: Mapping the debate (2016)Dissecting racial bias in an algorithm used to manage the health of populations (2019)Algorithmic Fairness: Choices, Assumptions, and Definitions (2020)
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References

  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 2014Big Data's Disparate Impact3,046 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2013Learning Fair Representations1,126 cited
  • 2018Fairness definitions explained1,125 cited
  • 2012Fairness-Aware Classifier with Prejudice Remover Regularizer694 cited
  • 2019Actionable Auditing650 cited
  • 2017Fairness Beyond Disparate Treatment & Disparate Impact630 cited
  • 2016Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment559 cited
  • 2017On Fairness and Calibration509 cited
  • 2017Optimized Pre-Processing for Discrimination Prevention459 cited
  • 2018Learning Adversarially Fair and Transferable Representations387 cited
  • 2018A Reductions Approach to Fair Classification364 cited
  • 2017Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations282 cited
  • 2019Path-Specific Counterfactual Fairness

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246 cited

Cited by

  • 2022Image fairness in deep learning: problems, models, and challenges19 cited
  • 2020FairNN - Conjoint Learning of Fair Representations for Fair Decisions17 cited
  • 2023Fix Fairness, Don’t Ruin Accuracy: Performance Aware Fairness Repair using AutoML15 cited