Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free

Haotao Wang, Tianlong Chen, Shupeng Gui, Ting-Kuei Hu, Ji Liu 0002, Zhangyang Wang. Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free. In Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, Hsuan-Tien Lin, editors, Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. 2020. [doi]

@inproceedings{WangCGH0W20,
  title = {Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free},
  author = {Haotao Wang and Tianlong Chen and Shupeng Gui and Ting-Kuei Hu and Ji Liu 0002 and Zhangyang Wang},
  year = {2020},
  url = {https://proceedings.neurips.cc/paper/2020/hash/537d9b6c927223c796cac288cced29df-Abstract.html},
  researchr = {https://researchr.org/publication/WangCGH0W20},
  cites = {0},
  citedby = {0},
  booktitle = {Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual},
  editor = {Hugo Larochelle and Marc'Aurelio Ranzato and Raia Hadsell and Maria-Florina Balcan and Hsuan-Tien Lin},
}