Auditing Differentially Private Machine Learning: How Private is Private SGD?

Matthew Jagielski, Jonathan R. Ullman, Alina Oprea. Auditing Differentially Private Machine Learning: How Private is Private SGD?. In Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, Hsuan-Tien Lin, editors, Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. 2020. [doi]

@inproceedings{JagielskiUO20,
  title = {Auditing Differentially Private Machine Learning: How Private is Private SGD?},
  author = {Matthew Jagielski and Jonathan R. Ullman and Alina Oprea},
  year = {2020},
  url = {https://proceedings.neurips.cc/paper/2020/hash/fc4ddc15f9f4b4b06ef7844d6bb53abf-Abstract.html},
  researchr = {https://researchr.org/publication/JagielskiUO20},
  cites = {0},
  citedby = {0},
  booktitle = {Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual},
  editor = {Hugo Larochelle and Marc'Aurelio Ranzato and Raia Hadsell and Maria-Florina Balcan and Hsuan-Tien Lin},
}