Adversarial Machine Learning with Double Oracle

IJCAI 2019 pp. 6472-6473

doi:10.24963/IJCAI.2019/925 /ijcai/2019/wang2019ijcai-adversarial/

Abstract

We aim to improve the general adversarial machine learning solution by introducing the double oracle idea from game theory, which is commonly used to solve a sequential zero-sum game, where the adversarial machine learning problem can be formulated as a zero-sum minimax problem between learner and attacker.

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Cite

Text

Wang. "Adversarial Machine Learning with Double Oracle." International Joint Conference on Artificial Intelligence, 2019. doi:10.24963/IJCAI.2019/925

Markdown

[Wang. "Adversarial Machine Learning with Double Oracle." International Joint Conference on Artificial Intelligence, 2019.](https://mlanthology.org/ijcai/2019/wang2019ijcai-adversarial/) doi:10.24963/IJCAI.2019/925

BibTeX

@inproceedings{wang2019ijcai-adversarial,
  title     = {{Adversarial Machine Learning with Double Oracle}},
  author    = {Wang, Kai},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2019},
  pages     = {6472-6473},
  doi       = {10.24963/IJCAI.2019/925},
  url       = {https://mlanthology.org/ijcai/2019/wang2019ijcai-adversarial/}
}