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Fast and Efficient MMD-Based Fair PCA via Optimization over Stiefel Manifold
16 references·0 citing·33 second hopsampled
Fast and Efficient MMD-Based Fair PCA via Optimization over Stiefel Manifold (2022)Fast and Efficient MMD-Based Fair PCA via…A Survey on Bias and Fairness in Machine Learning (2021)A Survey on Bias and Fairness…One-Network Adversarial Fairness (2019)One-Network Adversarial Fairn…Fair Algorithms for Clustering (2019)Fair Algorithms for ClusteringThe Price of Fair PCA: One Extra Dimension (2018)The Price of Fair PCA: One Ex…Learning Adversarially Fair and Transferable Representations (2018)Learning Adversarially Fair a…Optimized Pre-Processing for Discrimination Prevention (2017)Optimized Pre-Processing for …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 RepresentationsControlling Attribute Effect in Linear Regression (2013)Controlling Attribute Effect …Fairness through awareness (2012)Fairness through awarenessData preprocessing techniques for classification without discrimination (2011)Data preprocessing techniques…Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry (2006)Data mining to improve person…Data preparation for data mining (1999)Knowledge management and data mining for marketing (2001)Knowledge management technologies and applications—literature review from 1995 to 2002 (2003)A new TOPSIS-based multi-criteria approach to personnel selection (2009)Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming (2020)A review of machine learning applications in human resource management (2021)Fairness-Aware Classifier with Prejudice Remover Regularizer (2012)European Union Regulations on Algorithmic Decision Making and a “Right to Explanation” (2017)Semantics derived automatically from language corpora contain human-like biases (2017)Justice as Fairness: A Restatement (2002)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)Discrimination-aware data mining (2008)Classifying without discriminating (2009)Three naive Bayes approaches for discrimination-free classification (2010)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)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)A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle (2021)The Statistical Theory of Racism and Sexism. (1972)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)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)Gaydar: Facebook friendships expose sexual orientation (2009)Private traits and attributes are predictable from digital records of human behavior (2013)The ethics of algorithms: Mapping the debate (2016)Dissecting racial bias in an algorithm used to manage the health of populations (2019)Model Cards for Model Reporting (2019)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Bias in data‐driven artificial intelligence systems—An introductory survey (2020)
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References

  • 2021A Survey on Bias and Fairness in Machine Learning6,499 cited
  • 2012Fairness through awareness3,545 cited
  • 2014Big Data's Disparate Impact3,281 cited
  • 2016Equality of Opportunity in Supervised Learning2,733 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2011Data preprocessing techniques for classification without discrimination1,344 cited
  • 2013Learning Fair Representations1,155 cited
  • 2016Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment559 cited
  • 2017Optimized Pre-Processing for Discrimination Prevention472 cited
  • 2006Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry461 cited
  • 2018Learning Adversarially Fair and Transferable Representations431 cited
  • 2017Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations353 cited
  • 2013Controlling Attribute Effect in Linear Regression124 cited
  • 2019One-Network Adversarial Fairness95 cited
  • 2019Fair Algorithms for Clustering93 cited
  • 2018

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The Price of Fair PCA: One Extra Dimension
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