3 papers
cs.LG2026
Learning Sparse Decision Trees via Transformer Variational Auto-Encoders
Giacomo Fidone, Alessio Cascione, Riccardo Guidotti
Decision trees are among the most widely used models in machine learning, largely due to their transparent decision logic, making them well-suited for high-stakes decision-making c…
cs.LG2026
Expanding Data-Agnostic Pivotal Instances Selection Models with Proximity Trees and Ensemble Learning
Alessio Cascione, Mattia Setzu, Cristiano Landi +2
As decision-making processes grow more complex, machine learning tools have become essential for tackling business and societal challenges. However, many existing methods rely on d…
cs.AI2025
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…