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Editorial

• 
  Aleksandra B. Slavkovic, Adam D. Smith:
  Special Issue on Statistical and Learning-Theoretic Challenges in Data Privacy.

Articles

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

Editorial

• 
  Stephen E. Fienberg:
  Is the Privacy of Network Data an Oxymoron?

Articles

• 
  Fred Stutzman, Ralph Gross, Alessandro Acquisti:
  Silent Listeners: The Evolution of Privacy and Disclosure on Facebook.
• 
  Robert J. Hall, Larry A. Wasserman, Alessandro Rinaldo:
  Random Differential Privacy.
• 
  Yan-Xia Lin, Phillip Wise:
  Estimation of Regression Parameters from Noise Multiplied Data.
• 
  Consumer Data Privacy in a Networked World: A Framework for Protecting Privacy and Promoting Innovation in the Global Digital Economy.

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last updated on 2024-11-05 21:02 CET by the dblp team

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