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Yu / Li / Xu / Goebel / King

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

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ca. 53,49 €

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Fachbuch

Buch. Softcover

2025

400 S. Bibliographien.

In englischer Sprache

Springer. ISBN 978-3-031-82239-1

Format (B x L): 15,5 x 23,5 cm

Das Werk ist Teil der Reihe: Lecture Notes in Artificial Intelligence Lecture Notes in Computer Science; 15501

Produktbeschreibung

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.