2 citations · 4 across the 4 of their papers we have counts for
4 papers
Factorized AdaBoost.MH Achieves the Same Convergence Rate as AdaBoost.MH
Xin Zou, Jingyuan Xu
{AdaBoost.MH} reduces multi-class classification to a collection of binary subproblems and enjoys the classical boosting-type convergence guarantee under a weak learning condition.…
Reinforcement Learning Disrupts Gradient-Based Adversarial Optimization
Xinhai Zou, Chang Zhao, Alireza Aghabagherloo +3
Gradient-based adversarial attacks remain a dominant threat to deep neural networks (DNNs), as they exploit gradient information to efficiently optimize adversarial perturbations.…
Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data
Xin Zou, Weiwei Liu
Out-of-distribution (OOD) generalization has attracted increasing research attention in recent years, due to its promising experimental results in real-world applications. In this…
Generalization Bounds for Adversarial Contrastive Learning
Xin Zou, Weiwei Liu
Deep networks are well-known to be fragile to adversarial attacks, and adversarial training is one of the most popular methods used to train a robust model. To take advantage of un…