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An Axiomatic View of Statistical Privacy and Utility

Daniel Kifer, Bing-Rong Lin

Differentially Private Confidence Intervals for Empirical Risk Minimization

Yue Wang, Daniel Kifer, Jaewoo Lee

Per-instance Differential Privacy

Yu-Xiang Wang

How Uncertainty about Privacy and Confidentiality is Hampering Efforts to More Effectively Use Administrative Records in Producing U.S. National Statistics

Gerald W. Gates

Differential Privacy for Statistics: What we Know and What we Want to Learn

Cynthia Dwork, Adam Smith

Random Differential Privacy

Robert Hall, Larry Wasserman, Alessandro Rinaldo

Differential Privacy for Protecting Multi-dimensional Contingency Table Data: Extensions and Applications

Xiaolin Yang, Stephen E. Fienberg, Alessandro Rinaldo

An Evaluation Framework for Privacy-Preserving Record Linkage

Dinusha Vatsalan, Peter Christen, Christine M. O'Keefe, Vassilios S. Verykios

The Fienberg Problem: How to Allow Human Interactive Data Analysis in the Age of Differential Privacy

Cynthia Dwork, Jonathan Ullman

Privacy Protection from Sampling and Perturbation in Survey Microdata

Natalie Shlomo, Chris J. Skinner

Statistical Approximating Distributions Under Differential Privacy

Yue Wang, Daniel Kifer, Jaewoo Lee, Vishesh Karwa

Statistical Disclosure Limitation: New Directions and Challenges

Natalie Shlomo

A Privacy Preserving Algorithm to Release Sparse High-dimensional Histograms

Bai Li, Vishesh Karwa, Aleksandra Slavković, Rebecca Carter Steorts

Remembering Stephen Fienberg

Aleksandra Slavković, Lars Vilhuber

How Can We Analyze Differentially-Private Synthetic Datasets?

Anne-Sophie Charest

How Will Statistical Agencies Operate When All Data Are Private?

John M Abowd

Privacy-Preserving Data Sharing in High Dimensional Regression and Classification Settings

Stephen E. Fienberg, Jiashun Jin

A New Data Collection Technique for Preserving Privacy

Samuel S Wu, Shigang Chen, Deborah L Burr, Long Zhang

99-129

Privacy-Preserving Data Sharing for Genome-Wide Association Studies

Caroline Uhler, Aleksandra B. Slavkovic, Stephen E. Fienberg

Differentially Private Ordinary Least Squares

Or Sheffet

Differentially Private Inference for Binomial Data

Jordan Alexander Awan, Aleksandra Slavkovic

Toward a Reconceptualization of Confidentiality Protection in the Context of Linkages with Administrative Records

Stephen E. Fienberg

Is the Privacy of Network Data an Oxymoron?

Stephen E. Fienberg

Differentially private posterior summaries for linear regression coefficients

Gilad Amitai, Jerome Reiter

Partial Information Releases for Confidential Contingency Table Entries: Present and Future Research Efforts

Aleksandra B. Slavkovic
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about2

The Journal of Privacy and Confidentiality is an open-access multi-disciplinary journal whose purpose is to facilitate the coalescence of research methodologies and activities in the areas of privacy, confidentiality, and disclosure limitation. The JPC seeks to publish a wide range of research and review papers, not only from academia, but also from government (especially official statistical agencies) and industry, and to serve as a forum for exchange of views, discussion, and news. For more information, see the About the Journal page.

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