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Federated learning in the age of fou...

Yu, Han.

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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 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Federated learning in the age of foundation models - FL 2024 International Workshops/ edited by Han Yu ... [et al.].
其他題名:	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 /
其他題名:	FL 2024
其他作者:	Yu, Han.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xii, 182 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Federated learning (Machine learning) - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-82240-7
ISBN:	9783031822407

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 /
Federated learning in the age of foundation models - FL 2024 International WorkshopsFL@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 /[electronic resource] :FL 2024edited by Han Yu ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xii, 182 p. :ill. (chiefly color), digital ;24 cm. - Lecture notes in computer science,155011611-3349 ;. - Lecture notes in computer science ;15501..

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.

ISBN: 9783031822407

Standard No.: 10.1007/978-3-031-82240-7doiSubjects--Topical Terms:

3781523
Federated learning (Machine learning)
--Congresses.

LC Class. No.: Q325.65

Dewey Class. No.: 006.31

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