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Fair Clustering with Fair Correspondence Distribution
7 references·0 citing·18 second hop
Fair Clustering with Fair Correspondence Distribution (2021)Fair Clustering with Fair Correspondence …Learning Adversarially Fair and Transferable Representations (2018)Learning Adversarially Fair a…Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender Shades: Intersectional…From Parity to Preference-based Notions of Fairness in Classification (2017)From Parity to Preference-bas…Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Man is to Computer Programmer…Equality of Opportunity in Supervised Learning (2016)Equality of Opportunity in Su…Certifying and Removing Disparate Impact (2015)Certifying and Removing Dispa…Big Data's Disparate Impact (2014)Big Data's Disparate ImpactUniform Guidelines on Employee Selection Procedures (2007)Fairness through awareness (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)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)The role of artificial intelligence in achieving the Sustainable Development Goals (2020)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)50 Years of Test (Un)fairness: Lessons for Machine Learning (2018)Fairness without Demographics through Adversarially Reweighted Learning (2020)Algorithmic fairness datasets: the story so far (2022)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)The ethics of algorithms: Mapping the debate (2016)Dissecting racial bias in an algorithm used to manage the health of populations (2019)
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References

  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 2014Big Data's Disparate Impact3,046 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings1,615 cited
  • 2018Learning Adversarially Fair and Transferable Representations387 cited
  • 2017From Parity to Preference-based Notions of Fairness in Classification121 cited

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