Home > JOURNALS > JPC > Vol. 4 (2012) > Iss. 1
Special Issue on Statistical and Learning-Theoretic Challenges in Data Privacy
Article
Special Issue on Statistical and Learning-Theoretic Challenges in Data Privacy
Aleksandra B. Slavkovic and Adam Smith
An Axiomatic View of Statistical Privacy and Utility
Daniel Kifer and Bing-Rong Lin
Minimaxity, Statistical Thinking and Differential Privacy
Larry Wasserman
Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning
Benjamin I. P. Rubinstein, Peter L. Bartlett, Ling Huang, and Nina Taft
Differential Privacy for Protecting Multi-dimensional Contingency Table Data: Extensions and Applications
Xiaolin Yang, Stephen E. Fienberg, and Alessandro Rinaldo
Confidentialising Survival Analysis Output in a Remote Data Access System
Christine M. O'Keefe, Ross Stewart Sparks, Damien McAullay, and Bronwyn Loong
Privacy Protection from Sampling and Perturbation in Survey Microdata
Natalie Shlomo and Chris J. Skinner
Towards Providing Automated Feedback on the Quality of Inferences from Synthetic Datasets
David R. McClure and Jerome P. Reiter
Achieving Both Valid and Secure Logistic Regression Analysis on Aggregated Data from Different Private Sources
Yuval Nardi, Stephen E. Fienberg, and Robert J. Hall
Privacy-Preserving Data Sharing in High Dimensional Regression and Classification Settings
Stephen E. Fienberg and Jiashun Jin