1 citations · 1 across the 4 of their papers we have counts for
4 papers
Shared Vulnerabilities in Robustness-Optimized Defenses: One Breach Exposes the Family
Hanrui Wang, Ruihao Zheng, Shuo Wang +3
Adversarial robustness optimization aims to preserve correct prediction under adversarial perturbations, and has produced substantial robustness gains through methods such as adver…
Minimal Cascade Gradient Smoothing for Fast Transferable Preemptive Adversarial Defense
Hanrui Wang, Ching-Chun Chang, Chun-Shien Lu +3
Adversarial attacks persist as a major challenge in deep learning. While training- and test-time defenses are well-studied, they often reduce clean accuracy, incur high cost, or fa…
DeepiSign-G: Generic Watermark to Stamp Hidden DNN Parameters for Self-contained Tracking
Alsharif Abuadbba, Nicholas Rhodes, Kristen Moore +3
Deep learning solutions in critical domains like autonomous vehicles, facial recognition, and sentiment analysis require caution due to the severe consequences of errors. Research…
Learning with Mixture of Prototypes for Out-of-Distribution Detection
Haodong Lu, Dong Gong, Shuo Wang +3
Out-of-distribution (OOD) detection aims to detect testing samples far away from the in-distribution (ID) training data, which is crucial for the safe deployment of machine learnin…