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» An efficient clustering method for k-anonymization
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ICCD
2007
IEEE
157views Hardware» more  ICCD 2007»
14 years 5 months ago
Combining cluster sampling with single pass methods for efficient sampling regimen design
Microarchitectural simulation is orders of magnitude slower than native execution. As more elements are accurately modeled, problems associated with slow simulation are further ex...
Paul D. Bryan, Thomas M. Conte
EDBT
2008
ACM
124views Database» more  EDBT 2008»
14 years 8 months ago
An efficient clustering method for k-anonymization
The k-anonymity model is a privacy-preserving approach that has been extensively studied for the past few years. To minimize the information loss due to anonymization, it is cruci...
Jun-Lin Lin, Meng-Cheng Wei
PRL
2008
135views more  PRL 2008»
13 years 8 months ago
A hierarchical clustering algorithm based on the Hungarian method
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...
Jacob Goldberger, Tamir Tassa
AI
2006
Springer
14 years 9 days ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...
Ataul Bari, Luis Rueda
PAISI
2010
Springer
13 years 6 months ago
Efficient Privacy Preserving K-Means Clustering
Abstract. This paper introduces an efficient privacy-preserving protocol for distributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering i...
Maneesh Upmanyu, Anoop M. Namboodiri, Kannan Srina...