16 citations · 59 across the 13 of their papers we have counts for
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cs.LG2022★ 7 cited
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification
Quanshi Zhang, Xu Cheng, Yilan Chen +1
Compared to traditional learning from scratch, knowledge distillation sometimes makes the DNN achieve superior performance. This paper provides a new perspective to explain the suc…
cs.LG2022★ 2 cited
Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferability
Quanshi Zhang, Xin Wang, Jie Ren +4
Although many methods have been proposed to enhance the transferability of adversarial perturbations, these methods are designed in a heuristic manner, and the essential mechanism…
cs.LG2022★ 2 cited
Why Adversarial Training of ReLU Networks Is Difficult?
Xu Cheng, Hao Zhang, Yue Xin +3
This paper mathematically derives an analytic solution of the adversarial perturbation on a ReLU network, and theoretically explains the difficulty of adversarial training. Specifi…