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20212026
most citedGLocalX -- From Local to Global Explanations of Black Box AI Models

140 citations · 142 across the 7 of their papers we have counts for

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6 papers · 1 filter

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…

cs.LG2024

AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems

Clara Punzi, Roberto Pellungrini, Mattia Setzu +2

Everyday we increasingly rely on machine learning models to automate and support high-stake tasks and decisions. This growing presence means that humans are now constantly interact…

cs.LG2023

Correlation and Unintended Biases on Univariate and Multivariate Decision Trees

Mattia Setzu, Salvatore Ruggieri

Decision Trees are accessible, interpretable, and well-performing classification models. A plethora of variants with increasing expressiveness has been proposed in the last forty y…

cs.LG2023

Explainable Authorship Identification in Cultural Heritage Applications: Analysis of a New Perspective

Mattia Setzu, Silvia Corbara, Anna Monreale +2

While a substantial amount of work has recently been devoted to enhance the performance of computational Authorship Identification (AId) systems, little to no attention has been pa…

cs.LG2021140 cited

GLocalX -- From Local to Global Explanations of Black Box AI Models

Mattia Setzu, Riccardo Guidotti, Anna Monreale +3

Artificial Intelligence (AI) has come to prominence as one of the major components of our society, with applications in most aspects of our lives. In this field, complex and highly…