Lead federated neuromorphic learning for wireless edge artificial intelligence
Published 2022 View Full Article
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Title
Lead federated neuromorphic learning for wireless edge artificial intelligence
Authors
Keywords
-
Journal
Nature Communications
Volume 13, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2022-07-25
DOI
10.1038/s41467-022-32020-w
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- (2019) Eva García-Martín et al. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
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- (2018) Ken Chang et al. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
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