Federico MARCUZZI

Qualifica
Dottorando
Dottorato
INFORMATICA
36° Ciclo - Immatricolati nel 2020
Area tematica
DESIGN OF NEW MACHINE LEARNING BASED ALGORITHMS TO SOLVE RANKING PROBLEMS
Supervisore
Lucchese Claudio
E-mail
federico.marcuzzi@unive.it
853770@stud.unive.it
Sito web
www.unive.it/persone/federico.marcuzzi (scheda personale)
Struttura
Dipartimento di Scienze Ambientali, Informatica e Statistica
Sito web struttura: https://www.unive.it/dais

Pubblicazioni

Anno Tipologia Pubblicazione
Anno Tipologia Pubblicazione
2023 Articolo in Atti di convegno 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 - Scheda ARCA: 10278/5028100
2023 Articolo in Atti di convegno Marcuzzi F.; Lucchese C.; Orlando S. LambdaRank Gradients are Incoherent , CIKM 2023: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, Association for Computing Machinery, Inc, pp. 1777-1786, Convegno: 32nd ACM International Conference on Information and Knowledge Management, 2023 (ISBN 9798400701245)
DOI - Scheda ARCA: 10278/5044721
2023 Articolo in Atti di convegno Lucchese C.; Marcuzzi F.; Orlando S. On the Effect of Low-Ranked Documents: A New Sampling Function for Selective Gradient Boosting , Proceedings of the ACM Symposium on Applied Computing, Association for Computing Machinery, pp. 646-652, Convegno: 38th Annual ACM Symposium on Applied Computing, SAC 2023, 2023 (ISBN 9781450395175)
DOI - Scheda ARCA: 10278/5034901
2023 Abstract in Atti di convegno Lucchese C.; Marcuzzi F.; Orlando S. Does LambdaMART Do What You Expect? , CEUR Workshop Proceedings, CEUR-WS, vol. 3448, pp. 72, Convegno: 13th Italian Information Retrieval Workshop, IIR 2023, 2023 (ISSN 1613-0073)
- Scheda ARCA: 10278/5034902
2022 Articolo su rivista 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 - Scheda ARCA: 10278/5004095
2022 Articolo in Atti di convegno Marcuzzi F.; Lucchese C.; Orlando S. Filtering out Outliers in Learning to Rank , ICTIR 2022 - Proceedings of the 2022 ACM SIGIR International Conference on the Theory of Information Retrieval, Association for Computing Machinery, Inc, pp. 214-222, Convegno: 8th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2022, 2022 (ISBN 9781450394123)
DOI - Scheda ARCA: 10278/5004960
2022 Abstract in Atti di convegno Marcuzzi F.; Lucchese C.; Orlando S. SOUR: an Outliers Detection Algorithm in Learning to Rank (Abstract) , CEUR Workshop Proceedings, CEUR-WS, vol. 3177, Convegno: 12th Italian Information Retrieval Workshop, IIR 2022, 2022 (ISSN 1613-0073)
- Scheda ARCA: 10278/5004962
2021 Articolo su rivista Calzavara, Stefano; Lucchese, Claudio; Marcuzzi, Federico; Orlando, Salvatore Feature partitioning for robust tree ensembles and their certification in adversarial scenarios in EURASIP JOURNAL ON INFORMATION SECURITY, vol. 2021 (ISSN 2510-523X)
DOI - Scheda ARCA: 10278/3753807