6 citations · 9 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 3 cited
Robustness, Privacy, and Generalization of Adversarial Training
Fengxiang He, Shaopeng Fu, Bohan Wang +1
Adversarial training can considerably robustify deep neural networks to resist adversarial attacks. However, some works suggested that adversarial training might comprise the priva…
cs.LG2020★ 6 cited
Tighter Generalization Bounds for Iterative Differentially Private Learning Algorithms
Fengxiang He, Bohan Wang, Dacheng Tao
This paper studies the relationship between generalization and privacy preservation in iterative learning algorithms by two sequential steps. We first establish an alignment betwee…
cs.LG2020
Piecewise linear activations substantially shape the loss surfaces of neural networks
Fengxiang He, Bohan Wang, Dacheng Tao
Understanding the loss surface of a neural network is fundamentally important to the understanding of deep learning. This paper presents how piecewise linear activation functions s…