44 citations · 241 across the 27 of their papers we have counts for
Showing 2018Show all
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cs.LG2018★ 5 cited
Noisy Computations during Inference: Harmful or Helpful?
Minghai Qin, Dejan Vucinic
We study two aspects of noisy computations during inference. The first aspect is how to mitigate their side effects for naturally trained deep learning systems. One of the motivati…
cs.LG2018★ 2 cited
Training Recurrent Neural Networks against Noisy Computations during Inference
Minghai Qin, Dejan Vucinic
We explore the robustness of recurrent neural networks when the computations within the network are noisy. One of the motivations for looking into this problem is to reduce the hig…
cs.CV2018★ 14 cited
Densely Connected High Order Residual Network for Single Frame Image Super Resolution
Yiwen Huang, Ming Qin
Deep convolutional neural networks (DCNN) have been widely adopted for research on super resolution recently, however previous work focused mainly on stacking as many layers as pos…