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» When Random Sampling Preserves Privacy
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ICDM
2009
IEEE
223views Data Mining» more  ICDM 2009»
14 years 12 days ago
Differential Privacy for Clinical Trial Data: Preliminary Evaluations
—The concept of differential privacy as a rigorous definition of privacy has emerged from the cryptographic community. However, further careful evaluation is needed before we ca...
Duy Vu, Aleksandra Slavkovic
CVPR
2004
IEEE
14 years 7 months ago
Random Sampling LDA for Face Recognition
Linear Discriminant Analysis (LDA) is a popular feature extraction technique for face recognition. However, It often suffers from the small sample size problem when dealing with t...
Xiaogang Wang, Xiaoou Tang
SIGMOD
2005
ACM
128views Database» more  SIGMOD 2005»
14 years 5 months ago
Deriving Private Information from Randomized Data
Randomization has emerged as a useful technique for data disguising in privacy-preserving data mining. Its privacy properties have been studied in a number of papers. Kargupta et ...
Zhengli Huang, Wenliang Du, Biao Chen
SP
2008
IEEE
103views Security Privacy» more  SP 2008»
14 years 4 days ago
Preserving Caller Anonymity in Voice-over-IP Networks
— Applications such as VoIP need to provide anonymity to clients while maintaining low latency to satisfy quality of service (QoS) requirements. Existing solutions for providing ...
Mudhakar Srivatsa, Ling Liu, Arun Iyengar
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
14 years 5 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...