Training Effective Neural Networks on Structured Data with Federated Learning-Reference-Cited by-同舟云学术

Training Effective Neural Networks on Structured Data with Federated Learning

Published:2021 Issue: Volume: Page:394-406
ISSN:2367-3370
Container-title:Advanced Information Networking and Applications
language:
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Author:

Pustozerova Anastasia^ORCID,Rauber Andreas^ORCID,Mayer Rudolf^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-75075-6_32

Reference11 articles.

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2. Sheller, M.J., Reina, G.A., Edwards, B., Martin, J., Bakas, S.: Multi-institutional deep learning modeling without sharing patient data: a feasibility study on brain tumor segmentation. In: International Workshop on Brain Lesion (BrainLes), in conjunction with MICCAI (2018)

3. Rieke, N., Hancox, J., Li, W., et al.: The future of digital health with federated learning. NPJ Digit. Med. 3(1) (2020)

4. Konečný, J., McMahan, H.B., Yu, F.X. Richtárik, P., Suresh, A.T., Bacon, D.: Federated learning: strategies for improving communication efficiency. In: NIPS Workshop on Private Multi-Party Machine Learning (2016)

5. Nishio, T., Yonetani, R.: Client selection for federated learning with heterogeneous resources in mobile edge. In: IEEE International Conference on Communications (2019)

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