Federated Learning With Privacy-Preserving Ensemble Attention Distillation

Federated Learning (FL) is a machine learning paradigm where many local nodes collaboratively train a central model while keeping the training data decentralized. This is particularly relevant for clinical applications since patient data are usually not allowed to be transferred out of medical facil...

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Bibliographic Details
Published in:	IEEE transactions on medical imaging Vol. 42; no. 7; pp. 2057 - 2067
Main Authors:	Gong, Xuan, Song, Liangchen, Vedula, Rishi, Sharma, Abhishek, Zheng, Meng, Planche, Benjamin, Innanje, Arun, Chen, Terrence, Yuan, Junsong, Doermann, David, Wu, Ziyan
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.07.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Data models Distillation Federated learning Hospitals Humans Image classification Image processing Image reconstruction Image segmentation Leakage Machine Learning Privacy Risk reduction Servers Task analysis Training
ISSN:	0278-0062, 1558-254X, 1558-254X
Online Access:	Get full text
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