4 papers
Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
Shuang Liu, Yihan Wang, Yifan Zhu +2
Wasserstein distributionally robust optimization (WDRO) optimizes against worst-case distributional shifts within a specified uncertainty set, leading to enhanced generalization on…
Generalization Bound and New Algorithm for Clean-Label Backdoor Attack
Lijia Yu, Shuang Liu, Yibo Miao +2
The generalization bound is a crucial theoretical tool for assessing the generalizability of learning methods and there exist vast literatures on generalizability of normal learnin…
Game-Theoretic Unlearnable Example Generator
Shuang Liu, Yihan Wang, Xiao-Shan Gao
Unlearnable example attacks are data poisoning attacks aiming to degrade the clean test accuracy of deep learning by adding imperceptible perturbations to the training samples, whi…
Data-Dependent Stability Analysis of Adversarial Training
Yihan Wang, Shuang Liu, Xiao-Shan Gao
Stability analysis is an essential aspect of studying the generalization ability of deep learning, as it involves deriving generalization bounds for stochastic gradient descent-bas…