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cs.LG2023
Annealing Self-Distillation Rectification Improves Adversarial Training
Yu-Yu Wu, Hung-Jui Wang, Shang-Tse Chen
In standard adversarial training, models are optimized to fit one-hot labels within allowable adversarial perturbation budgets. However, the ignorance of underlying distribution sh…
cs.LG2023
Towards Large Certified Radius in Randomized Smoothing using Quasiconcave Optimization
Bo-Han Kung, Shang-Tse Chen
Randomized smoothing is currently the state-of-the-art method that provides certified robustness for deep neural networks. However, due to its excessively conservative nature, this…