%0 Journal Article %1 journals/jpc/McKennaMS21 %A McKenna, Ryan %A Miklau, Gerome %A Sheldon, Daniel %D 2021 %J J. Priv. Confidentiality %K dblp %N 3 %T Winning the NIST Contest: A scalable and general approach to differentially private synthetic data. %U http://dblp.uni-trier.de/db/journals/jpc/jpc11.html#McKennaMS21 %V 11

@article{journals/jpc/McKennaMS21, added-at = {2023-08-28T00:00:00.000+0200}, author = {McKenna, Ryan and Miklau, Gerome and Sheldon, Daniel}, biburl = {https://www.bibsonomy.org/bibtex/2114e940a49845585e18d6383d338f14e/dblp}, ee = {https://www.wikidata.org/entity/Q114585179}, interhash = {e657efa5fffcb9a559feb32a7d430ebf}, intrahash = {114e940a49845585e18d6383d338f14e}, journal = {J. Priv. Confidentiality}, keywords = {dblp}, number = 3, timestamp = {2024-04-08T11:25:10.000+0200}, title = {Winning the NIST Contest: A scalable and general approach to differentially private synthetic data.}, url = {http://dblp.uni-trier.de/db/journals/jpc/jpc11.html#McKennaMS21}, volume = 11, year = 2021 }