default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJournal of Privacy and Confidentiality, Volume 12
Volume 12, Number 1, July 2022
- Clément L. Canonne
, Gautam Kamath, Thomas Steinke:
Discrete Gaussian for Differential Privacy. - Georgios Kaissis, Moritz Knolle, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Daniel Rueckert:
Unified Interpretation of the Gaussian Mechanism for Differential Privacy Through the Sensitivity Index. - Anushka Vidanage, Thilina Ranbaduge, Peter Christen, Rainer Schnell:
Taxonomy of Attacks on Privacy-Preserving Record Linkage. - Mihai Budiu, Pratiksha Thaker, Parikshit Gopalan, Udi Wieder, Matei Zaharia:
Overlook: Differentially Private Exploratory Visualization for Big Data. - Michelle Nixon, Andrés F. Barrientos, Jerome P. Reiter, Aleksandra B. Slavkovic:
A Latent Class Modeling Approach for Differentially Private Synthetic Data for Contingency Tables.
Volume 12, Number 2, November 2022
- Christian Janos Lebeda, Martin Aumüller, Rasmus Pagh:
Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access. - Kobbi Nissim, Chao Yan:
The Sample Complexity of Distribution-Free Parity Learning in the Robust Shuffle Model. - Jonathan Hehir, Aleksandra B. Slavkovic, Xiaoyue Niu:
Consistent Spectral Clustering of Network Block Models under Local Differential Privacy. - Ruobin Gong:
Exact Inference with Approximate Computation for Differentially Private Data via Perturbations.
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-12-22 19:01 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
