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SemiPFL: Personalized Semi-Supervised Federated Learning Framework for Edge Intelligence. (arXiv:2203.08176v1 [cs.LG])
March 17, 2022, 1:20 a.m. | Arvin Tashakori, Wenwen Zhang, Z. Jane Wang, Peyman Servati
cs.CR updates on arXiv.org arxiv.org
Recent advances in wearable devices and Internet-of-Things (IoT) have led to
massive growth in sensor data generated in edge devices. Labeling such massive
data for classification tasks has proven to be challenging. In addition, data
generated by different users bear various personal attributes and edge
heterogeneity, rendering it impractical to develop a global model that adapts
well to all users. Concerns over data privacy and communication costs also
prohibit centralized data accumulation and training. This paper proposes a
novel personalized …
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