Beyond Local Sharpness: Communication-Efficient Global Sharpness-aware Minimization for Federated Learning.

Debora Caldarola, Pietro Cagnasso, Barbara Caputo, Marco Ciccone.

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.

Collaborative Visual Place Recognition through Federated Learning.

Mattia Dutto, Gabriele Berton, Debora Caldarola, Eros Fani, Gabriele Trivigno, Carlo Masone.

IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshop on Federated Learning for Computer Vision (CVPRW), 2024.

Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning.

Debora Caldarola, Barbara Caputo, Marco Ciccone.

International Conference on Computer Vision Workshop (ICCVW), 2023.

Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning.

Donald Shenaj*, Eros Fanì*, Marco Toldo, Debora Caldarola, Antonio Tavera, Umberto Michieli^†, Marco Ciccone^†, Pietro Zanuttigh^†, Barbara Caputo^†.

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023.

Improving Generalization in Federated Learning by Seeking Flat Minima.

Debora Caldarola*, Barbara Caputo, Marco Ciccone*.

European Conference on Computer Vision (ECCV), 2022.

FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving.

Lidia Fantauzzo*, Eros Fanì*, Debora Caldarola, Antonio Tavera, Fabio Cermelli, Marco Ciccone, Barbara Caputo.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022.

Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients.

Riccardo Zaccone*, Andrea Rizzardi*, Debora Caldarola, Marco Ciccone, Barbara Caputo.

26th International Conference on Pattern Recognition (ICPR), 2022.

Cluster-driven graph federated learning over multiple domains.

Debora Caldarola, Massimiliano Mancini, Fabio Galasso, Marco Ciccone, Emanuele Rodolà, Barbara Caputo.

IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshop on Learning from Limited and Imperfect Data (CVPRW), 2021.

Accelerating Federated Learning via Sequential Training of Grouped Heterogeneous Clients.

Andrea Silvi*, Andrea Rizzardi*, Debora Caldarola*, Marco Ciccone, Barbara Caputo.

IEEE Access

Efficiency and Generalization in Federated Learning: Insights from Sharpness-Aware Minimization.

Pietro Cagnasso.
Rel. Barbara Caputo, Debora Caldarola, Marco Ciccone.

Politecnico di Torino, Master's Degree in Data Science and Engineering, 2023.

Visual Transformers for Federated Learning: Exploring the Role of Architecture Layers in Generalization Enhancement.

Luca Marcellino.
Rel. Barbara Caputo, Debora Caldarola, Marco Ciccone.

Politecnico di Torino, Master's Degree in Data Science and Engineering, 2023.

Federated Visual Geo-Localization.

Mattia Dutto.
Rel. Barbara Caputo, Debora Caldarola, Marco Ciccone.

Politecnico di Torino, Master's Degree in Computer Engineering, 2023.

Speeding up convergence while preserving privacy in Heterogeneous Federated Learning.

Andrea Rizzardi.
Rel. Barbara Caputo, Debora Caldarola, Marco Ciccone.

Politecnico di Torino, Master's Degree in Data Science and Engineering, 2022.

Sequential to Parallel Federated Learning with Semantic-Aware Client Groupings.

Andrea Silvi.
Rel. Barbara Caputo, Debora Caldarola, Marco Ciccone.

Politecnico di Torino, Master's Degree in Data Science and Engineering, 2022.

On the Challenges of Class Imbalance in Federated Learning for Semantic Segmentation.

Eros Fanì.
Rel. Barbara Caputo, Debora Caldarola, Fabio Cermelli, Antonio Tavera.

Politecnico di Torino, Master's Degree in Data Science and Engineering, 2021.

On the Challenges of Federated Learning in Semantic Segmentation across Domains.

Lidia Fantauzzo.
Rel. Barbara Caputo, Debora Caldarola, Fabio Cermelli, Antonio Tavera.

Politecnico di Torino, Master's Degree in Mathematical Engineering, 2021.