123 citations · 163 across the 7 of their papers we have counts for
5 papers · 1 filter
Learning a Single Neuron for Non-monotonic Activation Functions
Lei Wu
We study the problem of learning a single neuron with gradient descent (GD). All the existing positive results are limited to the case…
The Generalization Error of the Minimum-norm Solutions for Over-parameterized Neural Networks
Weinan E, Chao Ma, Lei Wu
We study the generalization properties of minimum-norm solutions for three over-parametrized machine learning models including the random feature model, the two-layer neural networ…
A Priori Estimates of the Population Risk for Two-layer Neural Networks
Weinan E, Chao Ma, Lei Wu
New estimates for the population risk are established for two-layer neural networks. These estimates are nearly optimal in the sense that the error rates scale in the same way as t…
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects
Zhanxing Zhu, Jingfeng Wu, Bing Yu +2
Understanding the behavior of stochastic gradient descent (SGD) in the context of deep neural networks has raised lots of concerns recently. Along this line, we study a general for…
Understanding and Enhancing the Transferability of Adversarial Examples
Lei Wu, Zhanxing Zhu, Cheng Tai +1
State-of-the-art deep neural networks are known to be vulnerable to adversarial examples, formed by applying small but malicious perturbations to the original inputs. Moreover, the…