2 citations · 2 across the 3 of their papers we have counts for
6 papers
Reducing Flipping Errors in Deep Neural Networks
Xiang Deng, Yun Xiao, Bo Long +1
Deep neural networks (DNNs) have been widely applied in various domains in artificial intelligence including computer vision and natural language processing. A DNN is typically tra…
Learning with Retrospection
Xiang Deng, Zhongfei Zhang
Deep neural networks have been successfully deployed in various domains of artificial intelligence, including computer vision and natural language processing. We observe that the c…
Sparsity-Control Ternary Weight Networks
Xiang Deng, Zhongfei Zhang
Deep neural networks (DNNs) have been widely and successfully applied to various applications, but they require large amounts of memory and computational power. This severely restr…
Locally Linear Region Knowledge Distillation
Xiang Deng, Zhongfei, Zhang
Knowledge distillation (KD) is an effective technique to transfer knowledge from one neural network (teacher) to another (student), thus improving the performance of the student. T…
Deep Collective Learning: Learning Optimal Inputs and Weights Jointly in Deep Neural Networks
Xiang Deng, Zhongfei, Zhang
It is well observed that in deep learning and computer vision literature, visual data are always represented in a manually designed coding scheme (eg., RGB images are represented a…
Is the Meta-Learning Idea Able to Improve the Generalization of Deep Neural Networks on the Standard Supervised Learning?
Xiang Deng, Zhongfei Zhang
Substantial efforts have been made on improving the generalization abilities of deep neural networks (DNNs) in order to obtain better performances without introducing more paramete…