Latency-constrained DNN architecture learning for edge systems using zerorized batch normalization

Deep learning applications have been widely adopted on edge devices, to mitigate the privacy and latency issues of accessing cloud servers. Deciding the number of neurons during the design of a deep neural network to maximize performance is not intuitive. Particularly, many application scenarios are...

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書目詳細資料
Main Authors: Huai, Shuo, Liu, Di, Kong, Hao, Liu, Weichen, Subramaniam, Ravi, Makaya, Christian, Lin, Qian
其他作者: School of Computer Science and Engineering
格式: Article
語言:English
出版: 2023
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在線閱讀:https://hdl.handle.net/10356/165565
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