128 citations · 323 across the 15 of their papers we have counts for
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3 papers · 1 filter
cs.LG2020★ 28 cited
PECOS: Prediction for Enormous and Correlated Output Spaces
Hsiang-Fu Yu, Kai Zhong, Jiong Zhang +2
Many large-scale applications amount to finding relevant results from an enormous output space of potential candidates. For example, finding the best matching product from a large…
cs.LG2020★ 1 cited
Exploring the Potential of Low-bit Training of Convolutional Neural Networks
Kai Zhong, Xuefei Ning, Guohao Dai +5
In this work, we propose a low-bit training framework for convolutional neural networks, which is built around a novel multi-level scaling (MLS) tensor format. Our framework focuse…
cs.DC2020★ 1 cited
Enabling Efficient and Flexible FPGA Virtualization for Deep Learning in the Cloud
Shulin Zeng, Guohao Dai, Hanbo Sun +5
FPGAs have shown great potential in providing low-latency and energy-efficient solutions for deep neural network (DNN) inference applications. Currently, the majority of FPGA-based…