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Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3086623
Abstract: The Internet of Things (IoT) has significantly increased the number of terminals and network traffic. It is necessary to exploit the full capacity of the network and optimize content transfer. Despite the powerful processing and…
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Keywords:
federated deep;
reinforcement learning;
deep reinforcement;
hierarchical federated ... See more keywords
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Published in 2022 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2020.3005909
Abstract: Federated deep learning has been widely used in various fields. To protect data privacy, many privacy-preservingapproaches have been designed and implemented in various scenarios. However, existing works rarely consider a fundamental issue that the data…
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Keywords:
federated deep;
preserving federated;
irregular users;
privacy preserving ... See more keywords
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Published in 2022 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2022.3190557
Abstract: Indoor multi-robot communications face two key challenges: one is the severe signal strength degradation caused by blockages (e.g., walls) and the other is the dynamic environment caused by robot mobility. To address these issues, we…
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Keywords:
federated deep;
reinforcement learning;
deep reinforcement;
indoor multi ... See more keywords
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Published in 2023 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2022.3212966
Abstract: Jamming attack is one of the serious security breaches in the upcoming fifth-generation heterogeneous networks (5G HetNets). Most of the existing anti-jamming techniques, such as frequency hopping (FH) and direct sequence spread spectrum (DSSS) lack…
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Keywords:
federated deep;
reinforcement learning;
reinforcement;
deep reinforcement ... See more keywords