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Unsupervised Learning of Debiased Representations with Pseudo-Attributes
12 references·1 citing·41 second hop
Unsupervised Learning of Debiased Representations with Pseudo-Attributes (2022)Unsupervised Learning of Debiased Represe…Distributionally Robust Losses for Latent Covariate Mixtures (2022)Distributionally Robust Losse…Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach (2021)Statistics of Robust Optimiza…REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets (2020)REVISE: A Tool for Measuring …Learning from Failure: Training Debiased Classifier from Biased Classifier (2020)Learning from Failure: Traini…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…Women Also Snowboard: Overcoming Bias in Captioning Models (2018)Women Also Snowboard: Overcom…The Frontiers of Fairness in Machine Learning (2018)The Frontiers of Fairness in …Empirical Risk Minimization under Fairness Constraints (2018)Empirical Risk Minimization u…Learning Fair Representations (2013)Learning Fair RepresentationsRobust Solutions of Optimization Problems Affected by Uncertain Probabilities (2012)Robust Solutions of Optimizat…BiasAdv: Bias-Adversarial Augmentation for Model Debiasing (2023)BiasAdv: Bias-Adversarial Aug…Maxmin expected utility with non-unique prior (1989)Coherent Measures of Risk (1999)Robust Optimization (2009)A practical guide to robust optimization (2015)Data-driven robust optimization (2017)Distributionally Robust Stochastic Optimization with Wasserstein Distance (2022)Fairness through awareness (2012)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)Optimization of conditional value-at-risk (2000)From Data to Decisions: Distributionally Robust Optimization Is Optimal (2020)Learning-Based Robust Optimization: Procedures and Statistical Guarantees (2020)Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality (2022)Certifying and Removing Disparate Impact (2015)Equality of Opportunity in Supervised Learning (2016)Identifying and Correcting Label Bias in Machine Learning (2019)Algorithmic fairness datasets: the story so far (2022)Towards algorithm auditing: managing legal, ethical and technological risks of AI, ML and associated algorithms (2024)On the (im)possibility of fairness (2016)Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations (2017)Learning Adversarially Fair and Transferable Representations (2018)An empirical characterization of fair machine learning for clinical risk prediction (2020)A clarification of the nuances in the fairness metrics landscape (2022)Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey (2023)Big Data's Disparate Impact (2014)Towards fairer datasets (2020)Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation (2020)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Climate Change, Environmental Disasters, and Health Inequities: The Underlying Role of Structural Inequalities (2022)Representation Bias in Data: A Survey on Identification and Resolution Techniques (2023)Comprehensive study of driver behavior monitoring systems using computer vision and machine learning techniques (2024)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Demographic Bias in Biometrics: A Survey on an Emerging Challenge (2020)Fairness in Deep Learning: A Computational Perspective (2020)A Survey on Bias and Fairness in Machine Learning (2021)Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content? (2022)Quantifying Societal Bias Amplification in Image Captioning (2022)Uncurated Image-Text Datasets: Shedding Light on Demographic Bias (2023)An Investigation of Critical Issues in Bias Mitigation Techniques (2022)Overwriting Pretrained Bias with Finetuning Data (2023)
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References

  • 2013Learning Fair Representations1,126 cited
  • 2012Robust Solutions of Optimization Problems Affected by Uncertain Probabilities752 cited
  • 2018Women Also Snowboard: Overcoming Bias in Captioning Models404 cited
  • 2019Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations355 cited
  • 2018The Frontiers of Fairness in Machine Learning233 cited
  • 2019REPAIR: Removing Representation Bias by Dataset Resampling228 cited
  • 2021Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach195 cited
  • 2018Empirical Risk Minimization under Fairness Constraints157 cited
  • 2020An Investigation of Why Overparameterization Exacerbates Spurious Correlations122 cited
  • 2020REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets72 cited
  • 2020Learning from Failure: Training Debiased Classifier from Biased Classifier58 cited
  • 2022Distributionally Robust Losses for Latent Covariate Mixtures41 cited

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  • 2023BiasAdv: Bias-Adversarial Augmentation for Model Debiasing26 cited

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