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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.LG2025
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…