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Toward fair graph neural networks via real counterfactual samples
14 references·0 citing·40 second hop
Toward fair graph neural networks via real counterfactual samples (2024)Toward fair graph neural networks via rea…Fairness in Graph Mining: A Survey (2023)Fairness in Graph Mining: A S…Longitudinal Fairness with Censorship (2022)Longitudinal Fairness with Ce…Learning Fair Node Representations with Graph Counterfactual Fairness (2022)Learning Fair Node Representa…Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information (2021)Say No to the Discrimination:…A Survey on Bias and Fairness in Machine Learning (2021)A Survey on Bias and Fairness…On the apparent conflict between individual and group fairness (2020)On the apparent conflict betw…Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019)Social Data: Biases, Methodol…Fairwalk: Towards Fair Graph Embedding (2019)Fairwalk: Towards Fair Graph …FAHT: An Adaptive Fairness-aware Decision Tree Classifier (2019)FAHT: An Adaptive Fairness-aw…AMiner: Search and Mining of Academic Social Networks (2019)AMiner: Search and Mining of …Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…Fairness through awareness (2012)Fairness through awarenessThe comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients (2008)The comparisons of data minin…Statistical Classification Methods in Consumer Credit Scoring: A Review (1997)Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Machine Learning in Financial Crisis Prediction: A Survey (2011)Machine Learning in Banking Risk Management: A Literature Review (2019)A Review on Fairness in Machine Learning (2022)Incorporating Fairness into Game Theory and Economics (2011)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Princeton University Press (2017)Equality of Opportunity in Supervised Learning (2016)Dissecting racial bias in an algorithm used to manage the health of populations (2019)Fairness and Abstraction in Sociotechnical Systems (2019)Birds of a Feather: Homophily in Social Networks (2001)Designing and Conducting Mixed Methods Research (2010)Constructing grounded theory (2014)Detection and Resolution of Rumours in Social Media (2018)A Survey of Fake News (2020)Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges (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)Big Data's Disparate Impact (2014)EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks (2022)Representation Bias in Data: A Survey on Identification and Resolution Techniques (2023)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)Mapping the Margins: Intersectionality, Identity Politics, and Violence against Women of Color (1991)What Is the Point of Equality? (1999)An empirical characterization of fair machine learning for clinical risk prediction (2020)A clarification of the nuances in the fairness metrics landscape (2022)Fairness in recommender systems: research landscape and future directions (2023)Certifying and Removing Disparate Impact (2015)Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage (2022)A Theory of Justice (1971)The Filter Bubble: What the Internet Is Hiding from You (2011)Fairness and Bias in Algorithmic Hiring: A Multidisciplinary Survey (2024)Policy advice and best practices on bias and fairness in AI (2024)
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References

  • 2021A Survey on Bias and Fairness in Machine Learning5,798 cited
  • 2012Fairness through awareness3,501 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,157 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2008The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients881 cited
  • 2019Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries762 cited
  • 2020On the apparent conflict between individual and group fairness312 cited
  • 2021Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information247 cited
  • 2019Fairwalk: Towards Fair Graph Embedding163 cited
  • 2023Fairness in Graph Mining: A Survey138 cited
  • 2019FAHT: An Adaptive Fairness-aware Decision Tree Classifier85 cited
  • 2022Learning Fair Node Representations with Graph Counterfactual Fairness80 cited
  • 2019AMiner: Search and Mining of Academic Social Networks79 cited
  • 2022Longitudinal Fairness with Censorship35 cited

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