Lorenzo CAZZARO

Calzavara S.; Cazzaro L.; Lucchese C.; Marcuzzi F. Explainable Global Fairness Verification of Tree-Based Classifiers , Proceedings - 2023 IEEE Conference on Secure and Trustworthy Machine Learning, SaTML 2023, Institute of Electrical and Electronics Engineers Inc., pp. 1-17, Convegno: 2023 IEEE Conference on Secure and Trustworthy Machine Learning, SaTML 2023, 2023 (ISBN 978-1-6654-6299-0)
DOI 2023, Article in Conference Proceedings - ARCA card: 10278/5028100

Calzavara S.; Cazzaro L.; Pibiri G.E.; Prezza N. Verifiable Learning for Robust Tree Ensembles , CCS 2023 - Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, Association for Computing Machinery, Inc, pp. 1850-1864, Convegno: 30th ACM SIGSAC Conference on Computer and Communications Security, CCS 2023, 2023 (ISBN 9798400700507)
DOI 2023, Article in Conference Proceedings - ARCA card: 10278/5046160

Calzavara S.; Cazzaro L.; Lucchese C.; Marcuzzi F.; Orlando S. Beyond robustness: Resilience verification of tree-based classifiers in COMPUTERS & SECURITY, vol. 121, pp. 102843 (ISSN 0167-4048)
DOI 2022, Journal Article - ARCA card: 10278/5004095

Calzavara S.; Cazzaro L.; Lucchese C. AMEBA: An Adaptive Approach to the Black-Box Evasion of Machine Learning Models , ASIA CCS 2021 - Proceedings of the 2021 ACM Asia Conference on Computer and Communications Security, Association for Computing Machinery, Inc, pp. 292-306, Convegno: 16th ACM Asia Conference on Computer and Communications Security, ASIA CCS 2021, 2021 (ISBN 9781450382878)
DOI 2021, Article in Conference Proceedings - ARCA card: 10278/3742611

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