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Addressing bias in bagging and boosting regression models
15 references·0 citing·44 second hop
Addressing bias in bagging and boosting regression models (2024)Addressing bias in bagging and boosting r…Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey (2023)Bias Mitigation for Machine L…Ethics of Data and Analytics (2022)Ethics of Data and AnalyticsPutting Fairness Principles into Practice (2019)Putting Fairness Principles i…Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making (2019)Learning Optimal and Fair Dec…FAE: A Fairness-Aware Ensemble Framework (2019)FAE: A Fairness-Aware Ensembl…Counterfactual Fairness in Text Classification through Robustness (2019)Counterfactual Fairness in Te…Fairness definitions explained (2018)Fairness definitions explainedFair Forests (2018)Fair ForestsFairness Beyond Disparate Treatment & Disparate Impact (2017)Fairness Beyond Disparate Tre…Controlling Attribute Effect in Linear Regression (2013)Controlling Attribute Effect …Fairness through awareness (2012)Fairness through awarenessk-NN as an implementation of situation testing for discrimination discovery and prevention (2011)k-NN as an implementation of …Fairness-aware Learning through Regularization Approach (2011)Fairness-aware Learning throu…Data preprocessing techniques for classification without discrimination (2011)Data preprocessing techniques…Discrimination Aware Decision Tree Learning (2010)Discrimination Aware Decision…Discrimination-aware data mining (2008)Three naive Bayes approaches for discrimination-free classification (2010)A Reductions Approach to Fair Classification (2018)Fairness in Recommendation Ranking through Pairwise Comparisons (2019)A snapshot of the frontiers of fairness in machine learning (2020)The Economics of Discrimination (1971)The Economics of Discrimination. (1972)Classification with Fairness Constraints (2019)A Call to Action on Assessing and Mitigating Bias in Artificial Intelligence Applications for Mental Health (2022)A survey on datasets for fairness‐aware machine learning (2022)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)Semantics derived automatically from language corpora contain human-like biases (2017)Classifying without discriminating (2009)A Methodology for Direct and Indirect Discrimination Prevention in Data Mining (2012)Decision Theory for Discrimination-Aware Classification (2012)FA*IR (2017)Equality of Opportunity in Supervised Learning (2016)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)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)Learning Fair Representations (2013)Measuring and Mitigating Unintended Bias in Text Classification (2018)Towards Debiasing Sentence Representations (2020)Algorithmic fairness datasets: the story so far (2022)Towards trustworthy LLMs: a review on debiasing and dehallucinating in large language models (2024)Big Data's Disparate Impact (2014)Fairness of Exposure in Rankings (2018)Algorithmic Fairness: Choices, Assumptions, and Definitions (2020)Fairness in Machine Learning: A Survey (2023)Finite-time Analysis of the Multiarmed Bandit Problem (2002)Dissecting racial bias in an algorithm used to manage the health of populations (2019)A Survey on Bias and Fairness in Machine Learning (2021)A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers (2023)A Comprehensive Review of Bias in Deep Learning Models: Methods, Impacts, and Future Directions (2024)Policy advice and best practices on bias and fairness in AI (2024)Counterfactual Fairness (2017)Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)Artificial intelligence and people management: A critical assessment through the ethical lens (2022)How can we manage biases in artificial intelligence systems – A systematic literature review (2023)A Systematic Review on Fostering Appropriate Trust in Human-AI Interaction: Trends, Opportunities and Challenges (2024)
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References

  • 2012Fairness through awareness3,501 cited
  • 2011Data preprocessing techniques for classification without discrimination1,304 cited
  • 2018Fairness definitions explained1,125 cited
  • 2017Fairness Beyond Disparate Treatment & Disparate Impact630 cited
  • 2011Fairness-aware Learning through Regularization Approach375 cited
  • 2010Discrimination Aware Decision Tree Learning303 cited
  • 2011k-NN as an implementation of situation testing for discrimination discovery and prevention263 cited
  • 2022Ethics of Data and Analytics248 cited
  • 2023Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey222 cited
  • 2019Counterfactual Fairness in Text Classification through Robustness200 cited
  • 2019Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making135 cited
  • 2013Controlling Attribute Effect in Linear Regression124 cited
  • 2019Putting Fairness Principles into Practice112 cited
  • 2018Fair Forests55 cited
  • 2019FAE: A Fairness-Aware Ensemble Framework54 cited

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