176 citations · 339 across the 9 of their papers we have counts for
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cs.LG2020
Block-term Tensor Neural Networks
Jinmian Ye, Guangxi Li, Di Chen +3
Deep neural networks (DNNs) have achieved outstanding performance in a wide range of applications, e.g., image classification, natural language processing, etc. Despite the good pe…
cs.LG2017★ 17 cited
Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition
Jinmian Ye, Linnan Wang, Guangxi Li +4
Recurrent Neural Networks (RNNs) are powerful sequence modeling tools. However, when dealing with high dimensional inputs, the training of RNNs becomes computational expensive due…