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Fair Mixup: Fairness via Interpolation
7 references·8 citing·32 second hop
Fair Mixup: Fairness via Interpolation (2021)Fair Mixup: Fairness via InterpolationMitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Learning Adversarially Fair and Transferable Representations (2018)Learning Adversarially Fair a…Fairness in Criminal Justice Risk Assessments: The State of the Art (2018)Fairness in Criminal Justice …Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Fairness Constraints: Mechanisms for Fair Classification (2015)Fairness Constraints: Mechani…Learning Fair Representations (2013)Learning Fair RepresentationsFairness through awareness (2012)Fairness through awarenessMultiFair: Model Fairness With Multiple Sensitive Attributes (2024)MultiFair: Model Fairness Wit…Auditing and Generating Synthetic Data with Controllable Trust Trade-offs (2024)Auditing and Generating Synth…Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools (2023)Toward Operationalizing Pipel…Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling (2023)Multi-task learning with dyna…Why Knowledge Distillation Amplifies Gender Bias and How to Mitigate from the Perspective of DistilBERT (2022)Why Knowledge Distillation Am…Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers (2022)Leveling Down in Computer Vis…Learning Fair Classifiers with Partially Annotated Group Labels (2022)Learning Fair Classifiers wit…Improving fairness generalization through a sample-robust optimization method (2022)Improving fairness generaliza…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)Big Data's Disparate Impact (2014)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)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)FairGAN: Fairness-aware Generative Adversarial Networks (2018)Fairness in Recommendation Ranking through Pairwise Comparisons (2019)A snapshot of the frontiers of fairness in machine learning (2020)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)BiasAdv: Bias-Adversarial Augmentation for Model Debiasing (2023)FLAC: Fairness-Aware Representation Learning by Suppressing Attribute-Class Associations (2024)2013 IEEE International Conference on Big Data (2013)Dissecting racial bias in an algorithm used to manage the health of populations (2019)A Survey on Bias and Fairness in Machine Learning (2021)Public perception of accuracy-fairness trade-offs in algorithmic decisions in the United States (2025)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)Fairness definitions explained (2018)Algorithmic content moderation: Technical and political challenges in the automation of platform governance (2020)Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment (2016)Fairness Beyond Disparate Treatment & Disparate Impact (2017)Algorithmic Fairness: Choices, Assumptions, and Definitions (2020)Beyond ideals: why the (medical) AI industry needs to motivate behavioural change in line with fairness and transparency values, and how it can do it (2023)FairAdaBN: Mitigating Unfairness with Adaptive Batch Normalization and Its Application to Dermatological Disease Classification (2023)Gender Bias in Natural Language Processing and Computer Vision: A Comparative Survey (2024)
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References

  • 2012Fairness through awareness3,501 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2013Learning Fair Representations1,126 cited
  • 2018Fairness in Criminal Justice Risk Assessments: The State of the Art986 cited
  • 2015Fairness Constraints: Mechanisms for Fair Classification644 cited
  • 2018Learning Adversarially Fair and Transferable Representations387 cited

Cited by

  • 2022Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers44 cited
  • 2023Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling29 cited
  • 2022Learning Fair Classifiers with Partially Annotated Group Labels26 cited
  • 2022Improving fairness generalization through a sample-robust optimization method19 cited
  • 2023Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools19 cited
  • 2022Why Knowledge Distillation Amplifies Gender Bias and How to Mitigate from the Perspective of DistilBERT17 cited
  • 2024Auditing and Generating Synthetic Data with Controllable Trust Trade-offs15 cited

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2024
MultiFair: Model Fairness With Multiple Sensitive Attributes
13 cited