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Found 2 papers, 1 papers with code
Classification Utility, Fairness, and Compactness via Tunable Information Bottleneck and Rényi Measures
Designing machine learning algorithms that are accurate yet fair, not discriminating based on any sensitive attribute, is of paramount importance for society to accept AI for critical applications.
Renyi Fair Information Bottleneck for Image Classification
We develop a novel method for ensuring fairness in machine learning which we term as the Renyi Fair Information Bottleneck (RFIB).
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