Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization

Deokjae Lee, Seungyong Moon, Junhyeok Lee, Hyun Oh Song. Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization. In Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvári, Gang Niu 0001, Sivan Sabato, editors, International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA. Volume 162 of Proceedings of Machine Learning Research, pages 12478-12497, PMLR, 2022. [doi]

@inproceedings{LeeMLS22,
  title = {Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization},
  author = {Deokjae Lee and Seungyong Moon and Junhyeok Lee and Hyun Oh Song},
  year = {2022},
  url = {https://proceedings.mlr.press/v162/lee22h.html},
  researchr = {https://researchr.org/publication/LeeMLS22},
  cites = {0},
  citedby = {0},
  pages = {12478-12497},
  booktitle = {International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA},
  editor = {Kamalika Chaudhuri and Stefanie Jegelka and Le Song and Csaba Szepesvári and Gang Niu 0001 and Sivan Sabato},
  volume = {162},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}