Get started
Author

Federico Marcuzzi

Observed names: Marcuzzi F., Marcuzzi, Federico
ORCID: 0000-0002-8141-8294
Observed ORCID: 0000-0002-8141-8294
OpenAlex ID: A5009608294
Beyond robustness: Resilience verification of tree-based classifiers
2022 · Stefano Calzavara, Lorenzo Cazzaro, et al. · Computers & Security · 12
PDF
Feature partitioning for robust tree ensembles and their certification in adversarial scenarios
2021 · Stefano Calzavara, Claudio Lucchese, et al. · EURASIP Journal on Information Security · 10
PDF
Filtering out Outliers in Learning to Rank
2022 · Federico Marcuzzi, Claudio Lucchese, et al. · ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR) · 7
PDF
Software Systems Compliance with the AI Act
2024 · Teresa Scantamburlo, Paolo Falcarin, et al. · 6
LambdaRank Gradients are Incoherent
2023 · Federico Marcuzzi, Claudio Lucchese, et al. · ACM International Conference on Information and Knowledge Management (CIKM) · 4
PDF
Explainable Global Fairness Verification of Tree-Based Classifiers
2023 · Stefano Calzavara, Lorenzo Cazzaro, et al. · IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) · 3
PDF
How Quantization Shapes Bias in Large Language Models
2026 · Federico Marcuzzi, Xuefei Ning, et al. · Conference of the European Chapter of the Association for Computational Linguistics · 1
Investigating the Impact of Learner Errors on Social Bias in Large Language Models
2026 · Marcuzzi, Federico, Christoph, Martin, et al. · arXiv (Cornell University)
PDF
To Compare, or Not to Compare: On Methodological Practices in Evaluating Social Bias
2026 · Marcuzzi, Federico, Ning, Xuefei, et al. · arXiv (Cornell University)
PDF
How Quantization Shapes Bias in Large Language Models
2026 · Association for Computational Linguistics 2026, Gurevych, Iryna, et al. · Underline Science Inc.
Task S6_RT1.3 – Deliverable DS6_RT1.3.4 - Report on novel methodologies for optimal recommendation by empowering Machine Learning algorithms and Learning-to-Rank models
2025 · Marcuzzi, Federico, Lucchese, Claudio, et al. · Zenodo (CERN European Organization for Nuclear Research)
Machine Learning Methods for Ranking in Information Retrieval: When LambdaRank Gradient Incoherency Leads to Unfair Training
2025 · Marcuzzi, Federico, Lucchese, Claudio, et al. · Zenodo (CERN European Organization for Nuclear Research)
LambdaFair for Fair and Effective Ranking
2025 · Federico Marcuzzi, Claudio Lucchese, et al. · Lecture notes in computer science
Effective, Efficient, and Robust Learning Algorithms for Ranking and Classification
2024 · Federico Marcuzzi · ACM SIGIR Forum
On the Effect of Low-Ranked Documents: A New Sampling Function for Selective Gradient Boosting
2023 · Claudio Lucchese, Federico Marcuzzi, et al. · ACM Symposium on Applied Computing
PDF
Robust Tree Ensemble against Adversarial Examples
2020 · Federico Marcuzzi
Works count: 18
Citation count: 43
H-index: 4
I10-index: 2
Year
Topic
Type