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Giovanni Stilo

2 accepted papers

2025

How to Make Reproducible Research in Machine Unlearning with ERASURE

IJCAI 2025

Machine unlearning, the process of removing specific data influences from Machine Learning models, is critical for complying with regulations like the GDPR's right to be forgotten and addressing copyright disputes in large models. Despite its rising importance, the field still lacks standardized too

Cited by 0SourcePDFScholar
2024

Robust Stochastic Graph Generator for Counterfactual Explanations

AAAI 2024technical

Counterfactual Explanation (CE) techniques have garnered attention as a means to provide insights to the users engaging with AI systems. While extensively researched in domains such as medical imaging and autonomous vehicles, Graph Counterfactual Explanation (GCE) methods have been comparatively und…