BibTeX record conf/aaai/LiYWYH22

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@inproceedings{DBLP:conf/aaai/LiYWYH22,
  author       = {Maosen Li and
                  Yanhua Yang and
                  Kun Wei and
                  Xu Yang and
                  Heng Huang},
  title        = {Learning Universal Adversarial Perturbation by Adversarial Example},
  booktitle    = {Thirty-Sixth {AAAI} Conference on Artificial Intelligence, {AAAI}
                  2022, Thirty-Fourth Conference on Innovative Applications of Artificial
                  Intelligence, {IAAI} 2022, The Twelveth Symposium on Educational Advances
                  in Artificial Intelligence, {EAAI} 2022 Virtual Event, February 22
                  - March 1, 2022},
  pages        = {1350--1358},
  publisher    = {{AAAI} Press},
  year         = {2022},
  url          = {https://doi.org/10.1609/aaai.v36i2.20023},
  doi          = {10.1609/AAAI.V36I2.20023},
  timestamp    = {Sat, 30 Sep 2023 09:33:11 +0200},
  biburl       = {https://dblp.org/rec/conf/aaai/LiYWYH22.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}