14 citations · 29 across the 13 of their papers we have counts for
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cs.LG2019★ 14 cited
Towards Understanding the Importance of Noise in Training Neural Networks
Mo Zhou, Tianyi Liu, Yan Li +3
Numerous empirical evidence has corroborated that the noise plays a crucial rule in effective and efficient training of neural networks. The theory behind, however, is still largel…
cs.LG2019★ 8 cited
Inductive Bias of Gradient Descent based Adversarial Training on Separable Data
Yan Li, Ethan X. Fang, Huan Xu +1
Adversarial training is a principled approach for training robust neural networks. Despite of tremendous successes in practice, its theoretical properties still remain largely unex…