IJCNN’24 Special Session on Trustworthy Federated Learning in the Era of Foundation Models (FL@FM-IJCNN 2024)

Name: IJCNN’24 Special Session on Trustworthy Federated Learning in the Era of Foundation Models (FL@FM-IJCNN 2024)
Start: 2024-06-30
End: 2024-07-05

Federated Learning (FL) is an emerging machine learning paradigm that allows multiple end-users to collaboratively train models without sharing their private data. Existing FL frameworks are undergoing a significant change fueled by Foundation Models (FM), which presents a unique opportunity to unlock new possibilities, challenges, and applications in AI research. FL can be a beneficial tool to address the shortage of high-quality legalized data required by FM training. Meanwhile, FM can empower existing FL systems to alleviate performance degradation problems and lead to a better balance between generalization and personalization, diversity and fidelity. A robust, trustworthy FL platform can be established by examining the interplay between FL and FM, allowing them to benefit each other mutually. Also, it is necessary to overco

Date

30 Jun. 2024
05 Jul. 2024

City

Yokohama

Country

Japan

Topic Area

Engineering and Technology

IJCNN’24 Special Session on Trustworthy Federated Learning in the Era of Foundation Models (FL@FM-IJCNN 2024)

IJCNN’24 Special Session on Trustworthy Federated Learning in the Era of Foundation Models (FL@FM-IJCNN 2024)

Date

City

Country

Topic Area

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