Francesca Naretto

Orcid: 0000-0003-1301-7787

According to our database1, Francesca Naretto authored at least 26 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Interpreting Federated Learning by Aggregating SHAP Explanations.
IEEE Access, 2026

2025
Evaluating the Privacy Exposure of Interpretable Global and Local Explainers.
Trans. Data Priv., May, 2025

Optimizing and Tuning Fairness in Machine Learning: An Augmented Lagrangian Method with a Performance Budget.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

The Right to be Forgotten in the Age of AI: Legal, Philosophical, and Technical Challenges.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2025

Explainable AI methods and their interplay with privacy protection.
Proceedings of the 4th Italian Conference on Big Data and Data Science (ITADATA 2025), 2025

Differentially Private FastSHAP for Federated Learning Model Explainability.
Proceedings of the International Joint Conference on Neural Networks, 2025

AIL 2025: the 4th International Workshop on Imagining the AI Landscape After the AI Act (Preface).
Proceedings of the Workshops at the Fourth International Conference on Hybrid Human-Artificial Intelligence co-located with the Fourth International Conference on Hybrid Human-Artificial Intelligence (HHAI 2025), 2025

RAG-Enhanced LLMs for Interactive Explainability in Clinical Decision Support Systems.
Proceedings of the Artificial Intelligence for Healthcare, and Hybrid Models for Coupling Deductive and Inductive Reasoning, 2025

Enhancing Local Explanations with GAN-Based Neighborhood Generation.
Proceedings of the Discovery Science - 28th International Conference, 2025

2024
Stable and actionable explanations of black-box models through factual and counterfactual rules.
Data Min. Knowl. Discov., September, 2024

Analyzing and explaining privacy risks on time series data: ongoing work and challenges.
SIGKDD Explor., June, 2024

Balancing Act: Navigating the Privacy-Utility Spectrum in Principal Component Analysis.
Proceedings of the 21st International Conference on Security and Cryptography, 2024

Imagining the AI Landscape after the AI Act (Preface).
Proceedings of the Workshops at the Third International Conference on Hybrid Human-Artificial Intelligence co-located with (HHAI 2024), 2024

GLOR-FLEX: Local to Global Rule-Based EXplanations for Federated Learning.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2024

2023
Benchmarking and survey of explanation methods for black box models.
Data Min. Knowl. Discov., September, 2023

Agnostic Label-Only Membership Inference Attack.
Proceedings of the Network and System Security - 17th International Conference, 2023

EXPHLOT: EXplainable Privacy Assessment for Human LOcation Trajectories.
Proceedings of the Discovery Science - 26th International Conference, 2023

2022
Privacy Risk of Global Explainers.
Proceedings of the HHAI 2022: Augmenting Human Intellect, 2022

Monitoring Fairness in HOLDA.
Proceedings of the HHAI 2022: Augmenting Human Intellect, 2022

Evaluating the Privacy Exposure of Interpretable Global Explainers.
Proceedings of the 4th IEEE International Conference on Cognitive Machine Intelligence, 2022

Benchmark Analysis of Black Box Local Explanation Methods.
Proceedings of the 3rd Italian Workshop on Explainable Artificial Intelligence co-located with 21th International Conference of the Italian Association for Artificial Intelligence(AIxIA 2022), Udine, Italy, November 28, 2022

2021
A new approach for cross-silo federated learning and its privacy risks.
Proceedings of the 18th International Conference on Privacy, Security and Trust, 2021

Privacy Risk Assessment of Individual Psychometric Profiles.
Proceedings of the Discovery Science - 24th International Conference, 2021

Explainable for Trustworthy AI.
Proceedings of the Human-Centered Artificial Intelligence, 2021

2020
Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks.
Proceedings of the ECML PKDD 2020 Workshops, 2020

Predicting and Explaining Privacy Risk Exposure in Mobility Data.
Proceedings of the Discovery Science - 23rd International Conference, 2020


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