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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.
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