Riccardo Taiello

According to our database, Riccardo Taiello authored at least 18 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

DP-KFC: Data-Free Preconditioning for Privacy-Preserving Deep Learning.

Marc Molina Van De Bosch, Riccardo Taiello, Albert Sund Aillet, Andrea Protani, Miguel Ángel González Ballester, Luigi Serio

CoRR, May, 2026

Federated Transformer-GNN for Privacy-Preserving Brain Tumor Localization with Modality-Level Explainability.

Andrea Protani, Riccardo Taiello, Marc Molina Van De Bosch, Luigi Serio

Proceedings of the 19th International Joint Conference on Biomedical Engineering Systems and Technologies, 2026

2025

Federation of Agents: A Semantics-Aware Communication Fabric for Large-Scale Agentic AI.

Lorenzo Giusti, Ole Anton Werner, Riccardo Taiello, Matilde Carvalho Costa, Emre Tosun, Andrea Protani, Marc Molina, Rodrigo Lopes de Almeida, Paolo Cacace, Diogo Reis Santos, Luigi Serio

CoRR, September, 2025

Buffalo: A Practical Secure Aggregation Protocol for Asynchronous Federated Learning.

Riccardo Taiello, Clémentine Gritti, Melek Önen, Marco Lorenzi

IACR Cryptol. ePrint Arch., 2025

A Secure and Trustworthy Federated Learning Platform as a Service Model for Stroke Management in European Clinical Centers.

Diogo Reis Santos, Albert Sund Aillet, Antonio Boiano, Marco Di Gennaro, Riccardo Taiello, Usevalad Milasheuski, Lorenzo Giusti, Matilde Carvalho Costa, Mattia Brambilla, Paolo Cacace, Rodrigo Lopes De Almeida, Simone Buranti, Alessandro E. C. Redondi, Michele Carminati, Monica Nicoli, Sanaz Kianoush, Stefano Savazzi, Stefano Zanero, Luigi Serio

IEEE Access, 2025

Regional Hausdorff Distance Losses for Medical Image Segmentation.

Lisa Guzzi, Maria A. Zuluaga, Riccardo Taiello, Fabien Lareyre, Gilles Di Lorenzo, Sébastien Goffart, Andrea Chierici, Juliette Raffort, Hervé Delingette

Proceedings of the Machine Learning in Medical Imaging - 16th International Workshop, 2025

The Interplay Between Explainability and Differential Privacy in Federated Healthcare.

Marc Molina Van De Bosch, Andrea Protani, Riccardo Taiello, Lorenzo Giusti, Matilde Carvalho Costa, Ioannis Stathopoulos, Efstathios P. Efstathopoulos, Diogo Reis Santos, Miguel Ángel González Ballester, Luigi Serio

Proceedings of the Bridging Regulatory Science and Medical Imaging Evaluation; and Distributed, Collaborative, and Federated Learning, 2025

Buffalo: A Practical Secure Aggregation Protocol for Buffered Asynchronous Federated Learning.

Riccardo Taiello, Clémentine Gritti, Melek Önen, Marco Lorenzi

Proceedings of the Fifteenth ACM Conference on Data and Application Security and Privacy, 2025

2024

Privacy-preserving machine learning for large-scale collaborative healthcare data analysis. (Apprentissage automatique sécurisé pour l'analyse collaborative des données de santé à grande échelle).

Riccardo Taiello

PhD thesis, 2024

Privacy preserving image registration.

Riccardo Taiello, Melek Önen, Francesco Capano, Olivier Humbert, Marco Lorenzi

Medical Image Anal., 2024

Let Them Drop: Scalable and Efficient Federated Learning Solutions Agnostic to Client Stragglers.

Riccardo Taiello, Melek Önen, Clémentine Gritti, Marco Lorenzi

IACR Cryptol. ePrint Arch., 2024

Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications.

Riccardo Taiello, Sergen Cansiz, Marc Vesin, Francesco Cremonesi, Lucia Innocenti, Melek Önen, Marco Lorenzi

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 Workshops, 2024

Another Walk for Monchi.

Riccardo Taiello, Emre Tosun, Alberto Ibarrondo, Hervé Chabanne, Melek Önen

Proceedings of the Foundations and Practice of Security - 17th International Symposium, 2024

Let Them Drop: Scalable and Efficient Federated Learning Solutions Agnostic to Stragglers.

Riccardo Taiello, Melek Önen, Clémentine Gritti, Marco Lorenzi

Proceedings of the 19th International Conference on Availability, Reliability and Security, 2024

2023

Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications.

Francesco Cremonesi, Marc Vesin, Sergen Cansiz, Yannick Bouillard, Irene Balelli, Lucia Innocenti, Santiago Silva, Samy-Safwan Ayed, Riccardo Taiello, Laetitia Kameni, Richard Vidal, Fanny Orlhac, Christophe Nioche, Nathan Lapel, Bastien Houis, Romain Modzelewski, Olivier Humbert, Melek Önen, Marco Lorenzi

CoRR, 2023

2022

Study on transfer learning capabilities for pneumonia classification in chest-x-rays images.

Danilo Avola, Andrea Bacciu, Luigi Cinque, Alessio Fagioli, Marco Raoul Marini, Riccardo Taiello

Comput. Methods Programs Biomed., 2022

Privacy Preserving Image Registration.

Riccardo Taiello, Melek Önen, Olivier Humbert, Marco Lorenzi

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Study on Transfer Learning Capabilities for Pneumonia Classification in Chest-X-Rays Image.

Danilo Avola, Andrea Bacciu, Luigi Cinque, Alessio Fagioli, Marco Raoul Marini, Riccardo Taiello

CoRR, 2021