17 citations · 17 across the 2 of their papers we have counts for
2 papers
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…