Time Complexity of Training DNNs With Parallel Computing for Wireless Communications
Deep neural networks (DNNs) have been widely used for learning various wireless communication policies. While DNNs have demonstrated the ability to reduce the time complexity of inference, their training often incurs a high computational cost. Since practical wireless systems require retraining due...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Open Journal of Vehicular Technology |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10830510/ |
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