140 citations · 147 across the 10 of their papers we have counts for
3 papers · 1 filter
Towards the Formalization of a Trustworthy AI for Mining Interpretable Models explOiting Sophisticated Algorithms
Riccardo Guidotti, Martina Cinquini, Marta Marchiori Manerba +2
Interpretable-by-design models are crucial for fostering trust, accountability, and safe adoption of automated decision-making models in real-world applications. In this paper we f…
Fair Clustering with Clusterlets
Mattia Setzu, Riccardo Guidotti
Given their widespread usage in the real world, the fairness of clustering methods has become of major interest. Theoretical results on fair clustering show that fairness enjoys tr…
Interpretable Machine Learning for Oral Lesion Diagnosis through Prototypical Instances Identification
Alessio Cascione, Mattia Setzu, Federico A. Galatolo +2
Decision-making processes in healthcare can be highly complex and challenging. Machine Learning tools offer significant potential to assist in these processes. However, many curren…