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Found 2 papers, 1 papers with code
InfoFair: Information-Theoretic Intersectional Fairness
The vast majority of the existing works on group fairness, with a few exceptions, primarily focus on debiasing with respect to a single sensitive attribute, despite the fact that the co-existence of multiple sensitive attributes (e. g., gender, race, marital status, etc.)
Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics
Machine learning models are currently being deployed in a variety of real-world applications where model predictions are used to make decisions about healthcare, bank loans, and numerous other critical tasks.
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