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Cong Xie, Oluwasanmi Koyejo and Indranil Gupta
Distributed machine learning is primarily motivated by the promise of increased computation power for accelerating training and mitigating privacy concerns. Unlike machine learning on a single device, distributed machine learning requires collaboration a...
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Christoffer Åleskog, Håkan Grahn and Anton Borg
As machine learning and AI continue to rapidly develop, and with the ever-closer end of Moore?s law, new avenues and novel ideas in architecture design are being created and utilized. One avenue is accelerating AI as close to the user as possible, i.e., ...
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Liang Jin, Zude Zhou, Kunlun Li, Guoliang Zhang, Quan Liu, Bitao Yao and Yilin Fang
Carbon fiber is becoming a key material for engineering applications due to its excellent comprehensive properties. The process parameter optimization is an important step in the polymerization process of carbon fiber production. At present, most of the ...
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Hyunjin Joo and Yujin Lim
Traffic congestion is a worsening problem owing to an increase in traffic volume. Traffic congestion increases the driving time and wastes fuel, generating large amounts of fumes and accelerating environmental pollution. Therefore, traffic congestion is ...
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Ali Alqahtani, Xianghua Xie and Mark W. Jones
Deep networks often possess a vast number of parameters, and their significant redundancy in parameterization has become a widely-recognized property. This presents significant challenges and restricts many deep learning applications, making the focus on...
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