Livello precedente |
Davide Leo. Federated Learning: Tackling Heterogeneous Network Challenges in Distributed Deep Learning. Rel. Barbara Caputo, Marco Ciccone, Eros Fani'. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024
Amirshayan Nasirimajd. Sequential Domain Generalisation for Egocentric Action Recognition. Rel. Giuseppe Bruno Averta, Chiara Plizzari, Simone Alberto Peirone, Marco Ciccone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024
Antonio De Cinque. Towards Temporal Consistency in Egocentric Object Detection for Open-Vocabulary Navigation. Rel. Giuseppe Bruno Averta, Claudia Cuttano, Gabriele Tiboni, Marco Ciccone. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2024
Pietro Cagnasso. Efficiency and Generalization in Federated Learning: Insights from Sharpness-Aware Minimization. Rel. Barbara Caputo, Debora Caldarola, Marco Ciccone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2023
Luca Marcellino. Visual Transformers for Federated Learning: Exploring the Role of Architecture Layers in Generalization Enhancement. Rel. Barbara Caputo, Debora Caldarola, Marco Ciccone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2023
Andrea Silvi. Sequential to Parallel Federated Learning with Semantic-Aware Client Groupings. Rel. Barbara Caputo, Debora Caldarola, Marco Ciccone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2022
Andrea Rizzardi. Speeding up convergence while preserving privacy in Heterogeneous Federated Learning. Rel. Barbara Caputo, Debora Caldarola, Marco Ciccone. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2022