132 citations · 524 across the 20 of their papers we have counts for
4 papers · 1 filter
Defective Convolutional Networks
Tiange Luo, Tianle Cai, Mengxiao Zhang +3
Robustness of convolutional neural networks (CNNs) has gained in importance on account of adversarial examples, i.e., inputs added as well-designed perturbations that are impercept…
Convergence of Adversarial Training in Overparametrized Neural Networks
Ruiqi Gao, Tianle Cai, Haochuan Li +3
Neural networks are vulnerable to adversarial examples, i.e. inputs that are imperceptibly perturbed from natural data and yet incorrectly classified by the network. Adversarial tr…
Adversarially Robust Generalization Just Requires More Unlabeled Data
Runtian Zhai, Tianle Cai, Di He +4
Neural network robustness has recently been highlighted by the existence of adversarial examples. Many previous works show that the learned networks do not perform well on perturbe…
Gram-Gauss-Newton Method: Learning Overparameterized Neural Networks for Regression Problems
Tianle Cai, Ruiqi Gao, Jikai Hou +5
First-order methods such as stochastic gradient descent (SGD) are currently the standard algorithm for training deep neural networks. Second-order methods, despite their better con…