Re-Thinking Model Robustness from Stability: A New Insight to Defend Adversarial Examples

Zhang et al. "Re-Thinking Model Robustness from Stability: A New Insight to Defend Adversarial Examples." Machine Learning, 2022. doi:10.1007/S10994-022-06186-9

[Zhang et al. "Re-Thinking Model Robustness from Stability: A New Insight to Defend Adversarial Examples." Machine Learning, 2022.](https://mlanthology.org/mlj/2022/zhang2022mlj-rethinking/) doi:10.1007/S10994-022-06186-9

@article{zhang2022mlj-rethinking,
  title     = {{Re-Thinking Model Robustness from Stability: A New Insight to Defend Adversarial Examples}},
  author    = {Zhang, Shufei and Huang, Kaizhu and Xu, Zenglin},
  journal   = {Machine Learning},
  year      = {2022},
  pages     = {2489-2513},
  doi       = {10.1007/S10994-022-06186-9},
  volume    = {111},
  url       = {https://mlanthology.org/mlj/2022/zhang2022mlj-rethinking/}
}