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Convex Formulations for Fair Principal Component Analysis
13 references·8 citing·28 second hop
Convex Formulations for Fair Principal Component Analysis (2019)Convex Formulations for Fair Principal Co…Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)Fairness in Criminal Justice …Optimized Pre-Processing for Discrimination Prevention (2017)Optimized Pre-Processing for …Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations (2017)Data Decisions and Theoretica…Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…On the relation between accuracy and fairness in binary classification (2015)On the relation between accur…Fairness Constraints: Mechanisms for Fair Classification (2015)Fairness Constraints: Mechani…Certifying and Removing Disparate Impact (2015)Certifying and Removing Dispa…Video Game Telemetry as a Critical Tool in the Study of Complex Skill Learning (2013)Video Game Telemetry as a Cri…Learning Fair Representations (2013)Learning Fair RepresentationsFairness through awareness (2012)Fairness through awarenessThe comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients (2008)The comparisons of data minin…A Novel Approach for Fair Principal Component Analysis Based on Eigendecomposition (2023)A Novel Approach for Fair Pri…Fast and Efficient MMD-Based Fair PCA via Optimization over Stiefel Manifold (2022)Fast and Efficient MMD-Based …Fairness-Aware Range Queries for Selecting Unbiased Data (2022)Fairness-Aware Range Queries …Efficient fair principal component analysis (2022)Efficient fair principal comp…FairOD: Fairness-aware Outlier Detection (2021)FairOD: Fairness-aware Outlie…Representativity Fairness in Clustering (2020)Representativity Fairness in …Fairness in Clustering with Multiple Sensitive Attributes (2019)Fairness in Clustering with M…A Distributed Fair Machine Learning Framework with Private Demographic Data Protection (2019)A Distributed Fair Machine Le…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)A Survey on Bias and Fairness in Machine Learning (2021)Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Machine Learning in Banking Risk Management: A Literature Review (2019)A Review on Fairness in Machine Learning (2022)Bias and Unfairness in Machine Learning Models: A Systematic Review on Datasets, Tools, Fairness Metrics, and Identification and Mitigation Methods (2023)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)Three naive Bayes approaches for discrimination-free classification (2010)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)Big Data's Disparate Impact (2014)Model Cards for Model Reporting (2019)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Inherent Trade-Offs in the Fair Determination of Risk Scores (2016)Dissecting racial bias in an algorithm used to manage the health of populations (2019)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Algorithmic Bias in Education (2021)On the Opportunities and Risks of Foundation Models (2021)Fair, Transparent, and Accountable Algorithmic Decision-making Processes (2017)Fairness Beyond Disparate Treatment & Disparate Impact (2017)Bias in data‐driven artificial intelligence systems—An introductory survey (2020)
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References

  • 2012Fairness through awareness3,545 cited
  • 2016Equality of Opportunity in Supervised Learning2,733 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,270 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,428 cited
  • 2013Learning Fair Representations1,155 cited
  • 2018Fairness in Criminal Justice Risk Assessments: The State of the Art1,031 cited
  • 2008The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients881 cited
  • 2015Fairness Constraints: Mechanisms for Fair Classification713 cited
  • 2017Optimized Pre-Processing for Discrimination Prevention472 cited
  • 2017Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations353 cited
  • 2013Video Game Telemetry as a Critical Tool in the Study of Complex Skill Learning92 cited
  • 2015On the relation between accuracy and fairness in binary classification88 cited

Cited by

  • 2022Efficient fair principal component analysis36 cited
  • 2021FairOD: Fairness-aware Outlier Detection

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28 cited
  • 2019A Distributed Fair Machine Learning Framework with Private Demographic Data Protection20 cited
  • 2019Fairness in Clustering with Multiple Sensitive Attributes20 cited
  • 2022Fairness-Aware Range Queries for Selecting Unbiased Data19 cited
  • 2023A Novel Approach for Fair Principal Component Analysis Based on Eigendecomposition17 cited
  • 2022Fast and Efficient MMD-Based Fair PCA via Optimization over Stiefel Manifold13 cited
  • 2020Representativity Fairness in Clustering12 cited