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MultiFair: Model Fairness With Multiple Sensitive Attributes
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MultiFair: Model Fairness With Multiple Sensitive Attributes (2024)MultiFair: Model Fairness With Multiple S…Fairness in Machine Learning: A Survey (2023)Fairness in Machine Learning:…Fair Mixup: Fairness via Interpolation (2021)Fair Mixup: Fairness via Inte…Fair Feature Distillation for Visual Recognition (2021)Fair Feature Distillation for…Fair Attribute Classification through Latent Space De-biasing (2021)Fair Attribute Classification…A Survey on Bias and Fairness in Machine Learning (2021)A Survey on Bias and Fairness…Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation (2020)Towards Fairness in Visual Re…Minimax Pareto Fairness: A Multi Objective Perspective (2020)Minimax Pareto Fairness: A Mu…Fairness by Learning Orthogonal Disentangled Representations (2020)Fairness by Learning Orthogon…FairBatch: Batch Selection for Model Fairness (2020)FairBatch: Batch Selection fo…On the Fairness of Disentangled Representations (2019)On the Fairness of Disentangl…Flexibly Fair Representation Learning by Disentanglement (2019)Flexibly Fair Representation …Fairness Constraints: A Flexible Approach for Fair Classification (2019)Fairness Constraints: A Flexi…Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness (2017)Preventing Fairness Gerrymand…Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Learning Fair Representations (2013)Learning Fair RepresentationsFairness through awareness (2012)Fairness through awarenessIncorporating 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)Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment (2016)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Learning Adversarially Fair and Transferable Representations (2018)Can AI Help Reduce Disparities in General Medical and Mental Health Care? (2019)Introduction to Multi-Armed Bandits (2019)Semantics derived automatically from language corpora contain human-like biases (2017)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)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)CRITICAL QUESTIONS FOR BIG DATA (2012)An Overview of Artificial Intelligence Ethics (2022)Trustworthy AI: From Principles to Practices (2022)Considerations for addressing bias in artificial intelligence for health equity (2023)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Understanding and Evaluating Racial Biases in Image Captioning (2021)Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation (2022)Algorithmic Decision Making and the Cost of Fairness (2017)Counterfactual Fairness (2017)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)Ethical Considerations in AI-Based Recruitment (2019)“Shortcuts” Causing Bias in Radiology Artificial Intelligence: Causes, Evaluation, and Mitigation (2023)Towards algorithm auditing: managing legal, ethical and technological risks of AI, ML and associated algorithms (2024)Algorithmic fairness datasets: the story so far (2022)AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023)A survey of recent methods for addressing AI fairness and bias in biomedicine (2024)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

  • 2021A Survey on Bias and Fairness in Machine Learning5,798 cited
  • 2012Fairness through awareness3,501 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2013Learning Fair Representations1,126 cited
  • 2023Fairness in Machine Learning: A Survey645 cited
  • 2017Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness403 cited
  • 2020Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation285 cited
  • 2019Flexibly Fair Representation Learning by Disentanglement186 cited
  • 2019Fairness Constraints: A Flexible Approach for Fair Classification184 cited
  • 2021Fair Attribute Classification through Latent Space De-biasing123 cited
  • 2020Fairness by Learning Orthogonal Disentangled Representations69 cited
  • 2020Minimax Pareto Fairness: A Multi Objective Perspective69 cited
  • 2021Fair Mixup: Fairness via Interpolation65 cited
  • 2021Fair Feature Distillation for Visual Recognition63 cited
  • 2020FairBatch: Batch Selection for Model Fairness56 cited
  • 2019On the Fairness of Disentangled Representations

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