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Toward fair graph neural networks via real counterfactual samples · Study

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ArticleToward fair graph neural networks via real counterfactual samples

Zichong Wang2024

Article2024

Toward fair graph neural networks via real counterfactual samples

Zichong Wang · Meikang Qiu A · Min Chen · Malek Ben Salem · Xin Yao · Wenbin Zhang

26 citations·0/0 files stored·Knowledge and Information Systems

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Ethics and Social Impacts of AI Privacy-Preserving Technologies in Data Advanced Graph Neural Networks

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References

2021A Survey on Bias and Fairness in Machine Learning 2012Fairness through awareness 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments 2018Mitigating Unwanted Biases with Adversarial Learning 2008The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients 2019Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries 2020On the apparent conflict between individual and group fairness 2021Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information

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Papers that cite the same references — the relational fallback while embeddings are still backfilling.

2023Mitigating Multisource Biases in Graph Neural Networks via Real Counterfactual Samplesother · 12 shared references 2023Fairness in Graph Mining: A Surveyarticle · 6 shared references 2025Fairness amidst non‐IID graph data: A literature reviewarticle · 6 shared references 2022Integrating Behavioral, Economic, and Technical Insights to Understand and Address Algorithmic Bias: A Human-Centric Perspectivearticle · 6 shared references 2024FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralizationother · 6 shared references 2022A Review on Fairness in Machine Learningarticle · 5 shared references

Details

Year2024

Typearticle

Published2024-07-15

VenueKnowledge and Information Systems

ISSN-L0219-1377

Languageen

Citations26

Files0 public / 0

ShelfEthics and Social Impacts of AI

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doi10.1007/s10115-024-02161-z

openalex_workW4400665779

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