Federated Learning via Attentive Margin of Semantic Feature Representations
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DOI: 10.1109/jiot.2022.3209865
Abstract: Federated learning (FL) in Internet of Things (IoT) systems enables distributed model training using a large corpus of decentralized training data dispersed among multiple IoT clients. In this distributed setting, system and statistical heterogeneity, in… read more here.
Keywords: federated learning; representations learned; via attentive; margin ... See more keywords
On the Linguistic Representational Power of Neural Machine Translation Models
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DOI: 10.1162/coli_a_00367
Abstract: Despite the recent success of deep neural networks in natural language processing and other spheres of artificial intelligence, their interpretability remains a challenge. We analyze the representations learned by neural machine translation (NMT) models at… read more here.
Keywords: machine translation; representations learned; translation; neural machine ... See more keywords