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Minimax Pareto Fairness: A Multi Objective Perspective
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Minimax Pareto Fairness: A Multi Objective Perspective (2020)Minimax Pareto Fairness: A Multi Objectiv…MultiFair: Model Fairness With Multiple Sensitive Attributes (2024)MultiFair: Model Fairness Wit…Enhancing the fairness of AI prediction models by Quasi-Pareto improvement among heterogeneous thyroid nodule population (2024)Enhancing the fairness of AI …A Multi-Objective Framework for Balancing Fairness and Accuracy in Debiasing Machine Learning Models (2024)A Multi-Objective Framework f…Out of Context: Investigating the Bias and Fairness Concerns of “Artificial Intelligence as a Service” (2023)Out of Context: Investigating…Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers (2022)Leveling Down in Computer Vis…Towards Unbiased and Accurate Deferral to Multiple Experts (2021)Towards Unbiased and Accurate…Fairness Measures for Machine Learning in Finance (2021)Fairness Measures for Machine…Adaptive Sampling for Minimax Fair Classification (2021)Adaptive Sampling for Minimax…Algorithms of Oppression (2018)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)A Survey on Bias and Fairness in Machine Learning (2021)Diversity in sociotechnical machine learning systems (2022)Human-AI Collaboration: The Effect of AI Delegation on Human Task Performance and Task Satisfaction (2023)Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey) (2024)Rank Correlation Methods. (1957)Finite-time Analysis of the Multiarmed Bandit Problem (2002)Fairness through awareness (2012)Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2016)Counterfactual Fairness (2017)Algorithmic Fairness (2023)Mitigating Algorithmic Bias Through Probability Calibration: A Case Study on Lead Generation Data (2025)Equality of Opportunity in Supervised Learning (2016)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)Dissecting racial bias in an algorithm used to manage the health of populations (2019)The global landscape of AI ethics guidelines (2019)Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics (2023)Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models (2023)Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs) (2025)Unpacking Trust Dynamics in the LLM Supply Chain: An Empirical Exploration to Foster Trustworthy LLM Production & Use (2025)RISK, RACE, AND RECIDIVISM: PREDICTIVE BIAS AND DISPARATE IMPACT* (2016)Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities (2020)Algorithmic fairness in artificial intelligence for medicine and healthcare (2023)Autonomous Self‐Evolving Research on Biomedical Data: The DREAM Paradigm (2025)
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Cited by

  • 2021Towards Unbiased and Accurate Deferral to Multiple Experts45 cited
  • 2022Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers44 cited
  • 2021Fairness Measures for Machine Learning in Finance31 cited
  • 2023Out of Context: Investigating the Bias and Fairness Concerns of “Artificial Intelligence as a Service”30 cited
  • 2024Enhancing the fairness of AI prediction models by Quasi-Pareto improvement among heterogeneous thyroid nodule population25 cited
  • 2021Adaptive Sampling for Minimax Fair Classification15 cited
  • 2024A Multi-Objective Framework for Balancing Fairness and Accuracy in Debiasing Machine Learning Models14 cited
  • 2024MultiFair: Model Fairness With Multiple Sensitive Attributes13 cited

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