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» Optimal randomization for privacy preserving data mining
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DKE
2008
106views more  DKE 2008»
13 years 7 months ago
Towards optimal k-anonymization
When releasing microdata for research purposes, one needs to preserve the privacy of respondents while maximizing data utility. An approach that has been studied extensively in re...
Tiancheng Li, Ninghui Li
ICDM
2006
IEEE
183views Data Mining» more  ICDM 2006»
14 years 1 months ago
Accelerating Newton Optimization for Log-Linear Models through Feature Redundancy
— Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of pot...
Arpit Mathur, Soumen Chakrabarti
KDD
2005
ACM
149views Data Mining» more  KDD 2005»
14 years 1 months ago
A distributed learning framework for heterogeneous data sources
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Srujana Merugu, Joydeep Ghosh
PAKDD
2001
ACM
104views Data Mining» more  PAKDD 2001»
14 years 7 days ago
Optimizing the Induction of Alternating Decision Trees
The alternating decision tree brings comprehensibility to the performance enhancing capabilities of boosting. A single interpretable tree is induced wherein knowledge is distribute...
Bernhard Pfahringer, Geoffrey Holmes, Richard Kirk...
SICHERHEIT
2010
13 years 5 months ago
A Malware Instruction Set for Behavior-Based Analysis
We introduce a new representation for monitored behavior of malicious software called Malware Instruction Set (MIST). The representation is optimized for effective and efficient a...
Philipp Trinius, Carsten Willems, Thorsten Holz, K...