Slingshot: Globally Favorable Local Updates for Federated Learning

Federated Learning (FL), as a promising distributed learning paradigm, is proposed to solve the contradiction between the data hunger of modern machine learning and the increasingly stringent need for data privacy. However, clients naturally present different distributions of their local data and in...

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Bibliographic Details
Published in:IEEE Open Journal of the Computer Society
Main Authors: Jialiang Liu, Huawei Huang, Chun Wang, Sicong Zhou, Ruixin Li, Zibin Zheng
Format: Article
Language:English
Published: IEEE 2024-01-01
Subjects:
Federated learning
data heterogeneity
catastrophic forgetting
model performance
Online Access:https://ieeexplore.ieee.org/document/10411043/

Internet

https://ieeexplore.ieee.org/document/10411043/

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