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Information-Theoretic Bias Reduction via Causal View of Spurious Correlation
16 references·1 citing·32 second hop
Information-Theoretic Bias Reduction via Causal View of Spurious Correlation (2022)Information-Theoretic Bias Reduction via …Unsupervised Learning of Debiased Representations with Pseudo-Attributes (2022)Unsupervised Learning of Debi…Learning Unbiased Representations via Mutual Information Backpropagation (2021)Learning Unbiased Representat…Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation (2020)Towards Fairness in Visual Re…An Investigation of Why Overparameterization Exacerbates Spurious Correlations (2020)An Investigation of Why Overp…REPAIR: Removing Representation Bias by Dataset Resampling (2019)REPAIR: Removing Representati…Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations (2019)Balanced Datasets Are Not Eno…Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints (2017)Men Also Like Shopping: Reduc…Data-Driven Discrimination at Work (2017)Data-Driven Discrimination at…Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Prediction with Model-Based Neutrality (2013)Prediction with Model-Based N…Fairness-Aware Classifier with Prejudice Remover Regularizer (2012)Fairness-Aware Classifier wit…Fairness through awareness (2012)Fairness through awarenessData preprocessing techniques for classification without discrimination (2011)Data preprocessing techniques…Making things happen: a theory of causal explanation (2004)Making things happen: a theor…Causal Structure Learning of Bias for Fair Affect Recognition (2023)Causal Structure Learning of …Discrimination-aware data mining (2008)Three naive Bayes approaches for discrimination-free classification (2010)Fair, Transparent, and Accountable Algorithmic Decision-making Processes (2017)Trustworthy Artificial Intelligence: A Review (2022)Fairness in Machine Learning: A Survey (2023)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)A Survey on Bias and Fairness in Machine Learning (2021)Big Data's Disparate Impact (2014)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Addressing bias in big data and AI for health care: A call for open science (2021)Semantics derived automatically from language corpora contain human-like biases (2017)Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science (2018)A Review on Fairness in Machine Learning (2022)Bias and Fairness in Large Language Models: A Survey (2024)The Cambridge handbook of thinking and reasoning (2005)Causal Mechanisms in the Social Sciences (2010)A network theory of mental disorders (2017)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)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)Demographic Bias in Biometrics: A Survey on an Emerging Challenge (2020)Fairness in Deep Learning: A Computational Perspective (2020)Investigating Bias and Fairness in Facial Expression Recognition (2020)Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases (2021)Trustworthy AI: A Computational Perspective (2022)
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References

  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 2012Fairness through awareness3,501 cited
  • 2004Making things happen: a theory of causal explanation3,371 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2011Data preprocessing techniques for classification without discrimination1,304 cited
  • 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints829 cited
  • 2012Fairness-Aware Classifier with Prejudice Remover Regularizer694 cited
  • 2019Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations355 cited
  • 2020Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation285 cited
  • 2019REPAIR: Removing Representation Bias by Dataset Resampling228 cited
  • 2017Data-Driven Discrimination at Work141 cited
  • 2020An Investigation of Why Overparameterization Exacerbates Spurious Correlations122 cited
  • 2022Unsupervised Learning of Debiased Representations with Pseudo-Attributes28 cited
  • 2021Learning Unbiased Representations via Mutual Information Backpropagation

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23 cited
  • 2013Prediction with Model-Based Neutrality21 cited
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    • 2023Causal Structure Learning of Bias for Fair Affect Recognition12 cited