Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

Hadi Salman, Jerry Li, Ilya P. Razenshteyn, Pengchuan Zhang, Huan Zhang, Sébastien Bubeck, Greg Yang. Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. In Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Edward A. Fox, Roman Garnett, editors, Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14 December 2019, Vancouver, BC, Canada. pages 11289-11300, 2019. [doi]

@inproceedings{SalmanLRZZBY19,
  title = {Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers},
  author = {Hadi Salman and Jerry Li and Ilya P. Razenshteyn and Pengchuan Zhang and Huan Zhang and Sébastien Bubeck and Greg Yang},
  year = {2019},
  url = {http://papers.nips.cc/paper/9307-provably-robust-deep-learning-via-adversarially-trained-smoothed-classifiers},
  researchr = {https://researchr.org/publication/SalmanLRZZBY19},
  cites = {0},
  citedby = {0},
  pages = {11289-11300},
  booktitle = {Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14 December 2019, Vancouver, BC, Canada},
  editor = {Hanna M. Wallach and Hugo Larochelle and Alina Beygelzimer and Florence d'Alché-Buc and Edward A. Fox and Roman Garnett},
}