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» Smooth sensitivity and sampling in private data analysis
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STOC
2007
ACM
112views Algorithms» more  STOC 2007»
14 years 5 months ago
Smooth sensitivity and sampling in private data analysis
We introduce a new, generic framework for private data analysis. The goal of private data analysis is to release aggregate information about a data set while protecting the privac...
Kobbi Nissim, Sofya Raskhodnikova, Adam Smith
TCC
2010
Springer
173views Cryptology» more  TCC 2010»
14 years 1 months ago
Bounds on the Sample Complexity for Private Learning and Private Data Release
Learning is a task that generalizes many of the analyses that are applied to collections of data, and in particular, collections of sensitive individual information. Hence, it is n...
Amos Beimel, Shiva Prasad Kasiviswanathan, Kobbi N...
KDD
2007
ACM
186views Data Mining» more  KDD 2007»
14 years 5 months ago
An Ad Omnia Approach to Defining and Achieving Private Data Analysis
We briefly survey several privacy compromises in published datasets, some historical and some on paper. An inspection of these suggests that the problem lies with the nature of the...
Cynthia Dwork
ML
2008
ACM
248views Machine Learning» more  ML 2008»
13 years 4 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
FOCS
2010
IEEE
13 years 2 months ago
A Multiplicative Weights Mechanism for Privacy-Preserving Data Analysis
Abstract--We consider statistical data analysis in the interactive setting. In this setting a trusted curator maintains a database of sensitive information about individual partici...
Moritz Hardt, Guy N. Rothblum