2 papers
cs.LG2024
Soften to Defend: Towards Adversarial Robustness via Self-Guided Label Refinement
Daiwei Yu, Zhuorong Li, Lina Wei +3
Adversarial training (AT) is currently one of the most effective ways to obtain the robustness of deep neural networks against adversarial attacks. However, most AT methods suffer…
cs.CV2023
On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm
Peng Sun, Bei Shi, Daiwei Yu +1
Contemporary machine learning requires training large neural networks on massive datasets and thus faces the challenges of high computational demands. Dataset distillation, as a re…