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Conformal Predictions for Probabilistically Robust Scalable Machine Learning Classification
Conformal predictions make it possible to define reliable and robust learning algorithms.
Probabilistic Safety Regions Via Finite Families of Scalable Classifiers
The notion of scalable classifiers is then exploited to link the tuning of machine learning with error control.
CONFIDERAI: a novel CONFormal Interpretable-by-Design score function for Explainable and Reliable Artificial Intelligence
Everyday life is increasingly influenced by artificial intelligence, and there is no question that machine learning algorithms must be designed to be reliable and trustworthy for everyone.
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