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[null,"1.","Record Nr.",null,"UNISA996647970203316"]
[null,null,"Autore",null,"Yu Han"]
[null,null,"Titolo",null,"Federated Learning in the Age of Foundation Models - FL 2024 International Workshops : FL@FM-WWW 2024, Singapore, May 14, 2024; FL@FM-ICME 2024, Niagara Falls, ON, Canada, July 15, 2024; FL@FM-IJCAI 2024, Jeju Island, South Korea, August 5, 2024; and FL@FM-NeurIPS 2024, Vancouver, BC, Canada, December 15, 2024, Revised Selected Papers / / edited by Han Yu, Xiaoxiao Li, Zenglin Xu, Randy Goebel, Irwin King"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"9783031822407"]
[{"$nulls":4},"9783031822391"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (295 pages)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 15501"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","This LNAI volume constitutes the post proceedings of International Federated Learning Workshops such as follows: FL@FM-WWW 2024, FL@FM-ICME 2024, FL@FM-IJCAI 2024 and FL@FM-NeurIPS 2024. This LNAI volume focuses on the following topics: Efficient Model Adaptation and Personalization, Data Heterogeneity and Incomplete Data, Integration of Specialized Neural Architectures, Frameworks and Tools for Federated Learning, Applications in Domain-Specific Contexts, Unsupervised and Lightweight Learning, and Causal Discovery and Black-Box Optimization. ."]