Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing

Ryan M. Rogers, Salil P. Vadhan, Hyun-Woo Lim, Marco Gaboardi. Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing. In Maria-Florina Balcan, Kilian Q. Weinberger, editors, Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016. Volume 48 of JMLR Workshop and Conference Proceedings, pages 2111-2120, JMLR.org, 2016. [doi]

@inproceedings{RogersVLG16,
  title = {Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing},
  author = {Ryan M. Rogers and Salil P. Vadhan and Hyun-Woo Lim and Marco Gaboardi},
  year = {2016},
  url = {http://jmlr.org/proceedings/papers/v48/rogers16.html},
  researchr = {https://researchr.org/publication/RogersVLG16},
  cites = {0},
  citedby = {0},
  pages = {2111-2120},
  booktitle = {Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016},
  editor = {Maria-Florina Balcan and Kilian Q. Weinberger},
  volume = {48},
  series = {JMLR Workshop and Conference Proceedings},
  publisher = {JMLR.org},
}