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 /
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 Heterogene...
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| Співавтор: | |
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| Інші автори: | , , , , |
| Формат: | Електронний ресурс eКнига |
| Мова: | Англійська |
| Опубліковано: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Редагування: | 1st ed. 2025. |
| Серія: | Lecture Notes in Artificial Intelligence,
15501 |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1007/978-3-031-82240-7 |
| Теги: |
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| Резюме: | 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. . |
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| Фізичний опис: | XII, 182 p. 52 illus., 50 illus. in color. online resource. |
| ISBN: | 9783031822407 |
| ISSN: | 2945-9141 ; |
| DOI: | 10.1007/978-3-031-82240-7 |