Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM

Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM. Ligett, K., Neel, S., Roth, A., Waggoner, B., & Wu, Z. S. In Guyon, I., von Luxburg, U., Bengio, S., Wallach, H. M., Fergus, R., Vishwanathan, S. V. N., & Garnett, R., editors, Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, pages 2566–2576, 2017.

Paper bibtex

@inproceedings{DBLP:conf/nips/LigettNRWW17,
  author       = {Katrina Ligett and
                  Seth Neel and
                  Aaron Roth and
                  Bo Waggoner and
                  Zhiwei Steven Wu},
  editor       = {Isabelle Guyon and
                  Ulrike von Luxburg and
                  Samy Bengio and
                  Hanna M. Wallach and
                  Rob Fergus and
                  S. V. N. Vishwanathan and
                  Roman Garnett},
  title        = {Accuracy First: Selecting a Differential Privacy Level for Accuracy
                  Constrained {ERM}},
  booktitle    = {Advances in Neural Information Processing Systems 30: Annual Conference
                  on Neural Information Processing Systems 2017, December 4-9, 2017,
                  Long Beach, CA, {USA}},
  pages        = {2566--2576},
  year         = {2017},
  url          = {https://proceedings.neurips.cc/paper/2017/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html},
  timestamp    = {Wed, 12 May 2021 01:00:00 +0200},
  biburl       = {https://dblp.org/rec/conf/nips/LigettNRWW17.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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