SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training

Diao, E.; Ding, J.; Tarokh, V.

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Citation Details

SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training

Award ID(s):: 2134148

PAR ID:: 10418635

Author(s) / Creator(s):: Diao, E.; Ding, J.; Tarokh, V.

Date Published:: 2022-01-01

Journal Name:: Advances in neural information processing systems

ISSN:: 1049-5258

Format(s):: Medium: X

Sponsoring Org:: National Science Foundation

Free Publicly Accessible Full Text
Accepted Manuscript
Conference Paper:
The DOI is not currently available.

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