statistiche ricercatore

Nome	#
Cluster-driven Graph Federated Learning over Multiple Domains, file e384c433-7fd7-d4b2-e053-9f05fe0a1d67	65
Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients, file e384c434-98fd-d4b2-e053-9f05fe0a1d67	20
FedDrive: Generalizing Federated Learning to Semantic Segmentation in Autonomous Driving, file 5c7c3237-e8cb-44c9-af8a-f64340b863e4	6
Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning, file 9fb51210-215d-4984-b227-b26de40adb7d	6
Accelerating Federated Learning via Sequential Training of Grouped Heterogeneous Clients, file 4e210ddf-23fd-41e4-85e3-f8bdc3deeaa7	3
Improving Generalization in Federated Learning by Seeking Flat Minima, file 8bc2bd70-40f9-43e7-9e3e-454788e0f153	3
Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning, file 1043357d-e7ab-4153-8d60-f106da24c487	2
Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning, file e9a0e65d-27f5-434c-97c8-7fbead4c0536	2
Window-based Model Averaging Improves Generalization in Heterogeneous Federated Learning, file 0af8bd57-c19f-41f7-a0d7-377ba823aef1	1
Improving Generalization in Federated Learning by Seeking Flat Minima, file 0b79170c-a4ef-4ab1-a818-7fb62c25cd33	1
Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients, file f874a8d0-d75c-4400-88c8-4d9d725cb412	1
Totale	110

	Totale	Lug	Ago	Sett	Ott	Nov	Dic	Gen	Feb	Mar	Apr	Mag	Giu
2020/2021	7	0	0	0	0	0	0	0	0	0	0	5	2
2021/2022	56	3	4	2	3	2	2	5	8	2	6	10	9
2022/2023	40	1	4	2	3	5	8	1	9	6	0	1	0
2023/2024	7	0	0	0	1	0	0	0	3	1	2	0	0
Totale													110

PORTO @ Archivio Istituzionale della Ricerca