12 citations · 40 across the 13 of their papers we have counts for
4 papers · 1 filter
Adversarially Robust Estimate and Risk Analysis in Linear Regression
Yue Xing, Ruizhi Zhang, Guang Cheng
Adversarially robust learning aims to design algorithms that are robust to small adversarial perturbations on input variables. Beyond the existing studies on the predictive perform…
On the Generalization Properties of Adversarial Training
Yue Xing, Qifan Song, Guang Cheng
Modern machine learning and deep learning models are shown to be vulnerable when testing data are slightly perturbed. Existing theoretical studies of adversarial training algorithm…
Directional Pruning of Deep Neural Networks
Shih-Kang Chao, Zhanyu Wang, Yue Xing +1
In the light of the fact that the stochastic gradient descent (SGD) often finds a flat minimum valley in the training loss, we propose a novel directional pruning method which sear…
Predictive Power of Nearest Neighbors Algorithm under Random Perturbation
Yue Xing, Qifan Song, Guang Cheng
We consider a data corruption scenario in the classical Nearest Neighbors (-NN) algorithm, that is, the testing data are randomly perturbed. Under such a scenario, the impac…