10 citations · 26 across the 8 of their papers we have counts for
4 papers · 1 filter
Beyond Robustness: Resilience Verification of Tree-Based Classifiers
Stefano Calzavara, Lorenzo Cazzaro, Claudio Lucchese +2
In this paper we criticize the robustness measure traditionally employed to assess the performance of machine learning models deployed in adversarial settings. To mitigate the limi…
EiFFFeL: Enforcing Fairness in Forests by Flipping Leaves
Seyum Assefa Abebe, Claudio Lucchese, Salvatore Orlando
Nowadays Machine Learning (ML) techniques are extensively adopted in many socially sensitive systems, thus requiring to carefully study the fairness of the decisions taken by such…
Feature Partitioning for Robust Tree Ensembles and their Certification in Adversarial Scenarios
Stefano Calzavara, Claudio Lucchese, Federico Marcuzzi +1
Machine learning algorithms, however effective, are known to be vulnerable in adversarial scenarios where a malicious user may inject manipulated instances. In this work we focus o…
Treant: Training Evasion-Aware Decision Trees
Stefano Calzavara, Claudio Lucchese, Gabriele Tolomei +2
Despite its success and popularity, machine learning is now recognized as vulnerable to evasion attacks, i.e., carefully crafted perturbations of test inputs designed to force pred…