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HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography
[article]
2020
arXiv
pre-print
Electroencephalography (EEG) classification techniques have been widely studied for human behavior and emotion recognition tasks. But it is still a challenging issue since the data may vary from subject to subject, may change over time for the same subject, and maybe heterogeneous. Recent years, increasing privacy-preserving demands poses new challenges to this task. The data heterogeneity, as well as the privacy constraint of the EEG data, is not concerned in previous studies. To fill this
arXiv:1909.05784v3
fatcat:tb5pqwxhufaxfogjoi4ivswkde