16 citations · 20 across the 5 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.LG2019★ 2 cited
DASNet: Dynamic Activation Sparsity for Neural Network Efficiency Improvement
Qing Yang, Jiachen Mao, Zuoguan Wang +1
To improve the execution speed and efficiency of neural networks in embedded systems, it is crucial to decrease the model size and computational complexity. In addition to conventi…
cs.LG2019★ 1 cited
Feedback Learning for Improving the Robustness of Neural Networks
Chang Song, Zuoguan Wang, Hai Li
Recent research studies revealed that neural networks are vulnerable to adversarial attacks. State-of-the-art defensive techniques add various adversarial examples in training to i…
cs.LG2019
Joint Regularization on Activations and Weights for Efficient Neural Network Pruning
Qing Yang, Wei Wen, Zuoguan Wang +1
With the rapid scaling up of deep neural networks (DNNs), extensive research studies on network model compression such as weight pruning have been performed for improving deploymen…