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 (Lecture Notes in Computer Science #15501)

By: and and and and

Sign Up Now! Already a Member? Log In
You must be logged into Bookshare to access this title. Learn about membership options, or view our freely available titles.

Synopsis
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.
Copyright:
2025

Book Details

Book Quality:
Publisher Quality
ISBN-13:
9783031822407
Related ISBNs:
9783031822391
Publisher:
Springer Nature Switzerland
Date of Addition:
Copyrighted By:
The Editor
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.
Edited by:
Han Yu
Edited by:
Xiaoxiao Li
Edited by:
Zenglin Xu
Edited by:
Randy Goebel
Edited by:
Irwin King

Reviews

No Rating Yet