2 papers
cs.LG2026
Adversarial Rademacher Complexity of Deep Neural Networks
Jiancong Xiao, Yanbo Fan, Ruoyu Sun +1
Deep neural networks (DNNs) are highly vulnerable to adversarial attacks. Ideally, a robust model should perform well on both perturbed training data and unseen perturbed test data…
cs.LG2025
Max-Sliced Wasserstein Distance and its use for GANs
Ishan Deshpande, Yuan-Ting Hu, Ruoyu Sun +6
Generative adversarial nets (GANs) and variational auto-encoders have significantly improved our distribution modeling capabilities, showing promise for dataset augmentation, image…