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iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making
16 references·16 citing·25 second hopsampled
iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making (2019)iFair: Learning Individually Fair Data Re…Fairness of Exposure in Rankings (2018)Fairness of Exposure in Ranki…Equity of Attention (2018)Equity of AttentionMeasuring Fairness in Ranked Outputs (2017)Measuring Fairness in Ranked …Fairness Beyond Disparate Treatment & Disparate Impact (2017)Fairness Beyond Disparate Tre…Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…FA*IR (2017)FA*IRCounterfactual Fairness (2017)Counterfactual FairnessAlgorithmic Decision Making and the Cost of Fairness (2017)Algorithmic Decision Making a…There is a blind spot in AI research (2016)There is a blind spot in AI r…Inherent Trade-Offs in the Fair Determination of Risk Scores (2016)Inherent Trade-Offs in the Fa…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…Learning Fair Representations (2013)Learning Fair RepresentationsFairness through awareness (2012)Fairness through awarenessDiscrimination-aware data mining (2008)Discrimination-aware data min…The statistical fairness field guide: perspectives from social and formal sciences (2022)The statistical fairness fiel…Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems (2022)Fairness in Ranking, Part II:…Fairness in Ranking, Part I: Score-Based Ranking (2022)Fairness in Ranking, Part I: …EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks (2022)EDITS: Modeling and Mitigatin…What's Fair About Individual Fairness? (2021)What's Fair About Individual …On the Applicability of Machine Learning Fairness Notions (2021)On the Applicability of Machi…Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and unfairness within data management and analytics systems (2021)Managing bias and unfairness …Machine learning fairness notions: Bridging the gap with real-world applications (2021)Machine learning fairness not…Individual Fairness for Graph Neural Networks (2021)Individual Fairness for Graph…I agree with the decision, but they didn't deserve this (2021)I agree with the decision, bu…Debiasing Career Recommendations with Neural Fair Collaborative Filtering (2021)Debiasing Career Recommendati…Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness (2021)Bridging Machine Learning and…A Survey of Bias in Machine Learning Through the Prism of Statistical Parity (2021)A Survey of Bias in Machine L…Fairness without Demographics through Adversarially Reweighted Learning (2020)Fairness without Demographics…Operationalizing individual fairness with pairwise fair representations (2019)Operationalizing individual f…DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring (2019)DGHNL: A new deep genetic hie…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)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)Big Data's Disparate Impact (2014)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Structural Equations with Latent Variables. (1991)Testing Structural Equation Models. (1995)Bias in data‐driven artificial intelligence systems—An introductory survey (2020)Fairness-Aware Classifier with Prejudice Remover Regularizer (2012)Fair, Transparent, and Accountable Algorithmic Decision-making Processes (2017)'It's Reducing a Human Being to a Percentage' (2018)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)Dissecting racial bias in an algorithm used to manage the health of populations (2019)Fairness and Abstraction in Sociotechnical Systems (2019)Fairness definitions explained (2018)Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)Machine behaviour (2019)Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)Algorithmic Fairness: Choices, Assumptions, and Definitions (2020)Fairness in Machine Learning: A Survey (2023)
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References

  • 2012Fairness through awareness3,501 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,157 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2017Algorithmic Decision Making and the Cost of Fairness1,149 cited
  • 2013Learning Fair Representations1,126 cited
  • 2017Counterfactual Fairness995 cited
  • 2016Inherent Trade-Offs in the Fair Determination of Risk Scores942 cited
  • 2008Discrimination-aware data mining676 cited
  • 2017Fairness Beyond Disparate Treatment & Disparate Impact630 cited
  • 2018Fairness of Exposure in Rankings607 cited
  • 2016Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment559 cited
  • 2016There is a blind spot in AI research549 cited
  • 2017FA*IR497 cited
  • 2017Measuring Fairness in Ranked Outputs378 cited
  • 2018Equity of Attention337 cited

Cited by

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  • 2019DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring152 cited
  • 2022EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks125 cited
  • 2020Fairness without Demographics through Adversarially Reweighted Learning117 cited
  • 2021Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and unfairness within data management and analytics systems97 cited
  • 2022Fairness in Ranking, Part I: Score-Based Ranking94 cited
  • 2021Individual Fairness for Graph Neural Networks92 cited
  • 2022Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems87 cited
  • 2019Operationalizing individual fairness with pairwise fair representations86 cited
  • 2021Debiasing Career Recommendations with Neural Fair Collaborative Filtering81 cited
  • 2021Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness79 cited
  • 2021What's Fair About Individual Fairness?74 cited
  • 2021On the Applicability of Machine Learning Fairness Notions72 cited
  • 2021Machine learning fairness notions: Bridging the gap with real-world applications60 cited
  • 2021I agree with the decision, but they didn't deserve this59 cited
  • 2022The statistical fairness field guide: perspectives from social and formal sciences51 cited
  • 2021A Survey of Bias in Machine Learning Through the Prism of Statistical Parity49 cited