#fair-ml News & Analysis

2 articles tagged with #fair-ml. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AINeutralarXiv – CS AI · Jun 236/10

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Causally Fair Node Classification on Non-IID Graph Data

Researchers developed MPVA, a machine learning framework that applies causal inference to achieve fairer node classification on graph data with non-independent distributions. The work addresses a critical gap in algorithmic fairness by accounting for causal heterogeneity in network structures, enabling better bias mitigation in real-world applications like social networks.

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AINeutralarXiv – CS AI · Jun 46/10

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Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods

Researchers extend null-space projection techniques for fairness in machine learning to kernel methods, enabling fair regression with continuous protected attributes. The method transforms kernel matrices directly and demonstrates competitive performance with Support Vector Regression across multiple datasets, advancing the limited field of continuous fairness in ML systems.

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