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» Using Anonymized Data for Classification
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APPROX
2008
Springer
101views Algorithms» more  APPROX 2008»
15 years 2 months ago
Streaming Algorithms for k-Center Clustering with Outliers and with Anonymity
Clustering is a common problem in the analysis of large data sets. Streaming algorithms, which make a single pass over the data set using small working memory and produce a cluster...
Richard Matthew McCutchen, Samir Khuller
84
Voted
SIGCOMM
2010
ACM
15 years 19 days ago
Privacy-preserving P2P data sharing with OneSwarm
Privacy--the protection of information from unauthorized disclosure--is increasingly scarce on the Internet, and yet increasingly important as every user becomes both a content co...
Tomas Isdal, Michael Piatek, Arvind Krishnamurthy,...
114
Voted
PVLDB
2008
146views more  PVLDB 2008»
14 years 12 months ago
Resisting structural re-identification in anonymized social networks
We identify privacy risks associated with releasing network data sets and provide an algorithm that mitigates those risks. A network consists of entities connected by links repres...
Michael Hay, Gerome Miklau, David Jensen, Donald F...
ICPR
2010
IEEE
14 years 10 months ago
Audio-Visual Classification and Fusion of Spontaneous Affective Data in Likelihood Space
This paper focuses on audio-visual (using facial expression, shoulder and audio cues) classification of spontaneous affect, utilising generative models for classification (i) in t...
Mihalis A. Nicolaou, Hatice Gunes, Maja Pantic
SIGMOD
2006
ACM
96views Database» more  SIGMOD 2006»
16 years 17 days ago
Injecting utility into anonymized datasets
Limiting disclosure in data publishing requires a careful balance between privacy and utility. Information about individuals must not be revealed, but a dataset should still be us...
Daniel Kifer, Johannes Gehrke