Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness

Lingjuan Lyu, Xuanli He, Yitong Li. Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness. In Trevor Cohn, Yulan He, Yang Liu, editors, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings, EMNLP 2020, Online Event, 16-20 November 2020. pages 2355-2365, Association for Computational Linguistics, 2020. [doi]

@inproceedings{LyuHL20-0,
  title = {Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness},
  author = {Lingjuan Lyu and Xuanli He and Yitong Li},
  year = {2020},
  url = {https://www.aclweb.org/anthology/2020.findings-emnlp.213/},
  researchr = {https://researchr.org/publication/LyuHL20-0},
  cites = {0},
  citedby = {0},
  pages = {2355-2365},
  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings, EMNLP 2020, Online Event, 16-20 November 2020},
  editor = {Trevor Cohn and Yulan He and Yang Liu},
  publisher = {Association for Computational Linguistics},
  isbn = {978-1-952148-90-3},
}