903 citations · 2.5k across the 78 of their papers we have counts for
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BT-Nets: Simplifying Deep Neural Networks via Block Term Decomposition
Guangxi Li, Jinmian Ye, Haiqin Yang +3
Recently, deep neural networks (DNNs) have been regarded as the state-of-the-art classification methods in a wide range of applications, especially in image classification. Despite…
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…
Unified Spectral Clustering with Optimal Graph
Zhao Kang, Chong Peng, Qiang Cheng +1
Spectral clustering has found extensive use in many areas. Most traditional spectral clustering algorithms work in three separate steps: similarity graph construction; continuous l…
Two Birds with One Stone: Transforming and Generating Facial Images with Iterative GAN
Dan Ma, Bin Liu, Zhao Kang +3
Generating high fidelity identity-preserving faces with different facial attributes has a wide range of applications. Although a number of generative models have been developed to…
Stochastic Sequential Neural Networks with Structured Inference
Hao Liu, Haoli Bai, Lirong He +1
Unsupervised structure learning in high-dimensional time series data has attracted a lot of research interests. For example, segmenting and labelling high dimensional time series c…