19 citations · 41 across the 5 of their papers we have counts for
14 papers
TRP: Trained Rank Pruning for Efficient Deep Neural Networks
Yuhui Xu, Yuxi Li, Shuai Zhang +6
To enable DNNs on edge devices like mobile phones, low-rank approximation has been widely adopted because of its solid theoretical rationale and efficient implementations. Several…
Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification
Huanrui Yang, Minxue Tang, Wei Wen +5
Modern deep neural networks (DNNs) often require high memory consumption and large computational loads. In order to deploy DNN algorithms efficiently on edge or mobile devices, a s…
Line Art Correlation Matching Feature Transfer Network for Automatic Animation Colorization
Zhang Qian, Wang Bo, Wen Wei +2
Automatic animation line art colorization is a challenging computer vision problem, since the information of the line art is highly sparse and abstracted and there exists a strict…
Neural Predictor for Neural Architecture Search
Wei Wen, Hanxiao Liu, Hai Li +3
Neural Architecture Search methods are effective but often use complex algorithms to come up with the best architecture. We propose an approach with three basic steps that is conce…
Trained Rank Pruning for Efficient Deep Neural Networks
Yuhui Xu, Yuxi Li, Shuai Zhang +7
To accelerate DNNs inference, low-rank approximation has been widely adopted because of its solid theoretical rationale and efficient implementations. Several previous works attemp…
Conditional Transferring Features: Scaling GANs to Thousands of Classes with 30% Less High-quality Data for Training
Chunpeng Wu, Wei Wen, Yiran Chen +1
Generative adversarial network (GAN) has greatly improved the quality of unsupervised image generation. Previous GAN-based methods often require a large amount of high-quality trai…