35 citations · 70 across the 20 of their papers we have counts for
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cs.LG2023
Ultra-low Precision Multiplication-free Training for Deep Neural Networks
Chang Liu, Rui Zhang, Xishan Zhang +5
The training for deep neural networks (DNNs) demands immense energy consumption, which restricts the development of deep learning as well as increases carbon emissions. Thus, the s…
cs.LG2020★ 1 cited
Scheduling Real-time Deep Learning Services as Imprecise Computations
Shuochao Yao, Yifan Hao, Yiran Zhao +6
The paper presents an efficient real-time scheduling algorithm for intelligent real-time edge services, defined as those that perform machine intelligence tasks, such as voice reco…