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» A Privacy Preserving Framework for Gaussian Mixture Models
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ICDM
2010
IEEE
160views Data Mining» more  ICDM 2010»
9 years 5 months ago
A Privacy Preserving Framework for Gaussian Mixture Models
Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
Madhusudana Shashanka
KDD
2004
ACM
159views Data Mining» more  KDD 2004»
10 years 1 months ago
Optimal randomization for privacy preserving data mining
Randomization is an economical and eļ¬ƒcient approach for privacy preserving data mining (PPDM). In order to guarantee the performance of data mining and the protection of individ...
Michael Yu Zhu, Lei Liu
PAMI
2006
215views more  PAMI 2006»
9 years 7 months ago
Bayesian Feature and Model Selection for Gaussian Mixture Models
We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...
AAAI
2011
8 years 7 months ago
User-Controllable Learning of Location Privacy Policies With Gaussian Mixture Models
With smart-phones becoming increasingly commonplace, there has been a subsequent surge in applications that continuously track the location of users. However, serious privacy conc...
Justin Cranshaw, Jonathan Mugan, Norman M. Sadeh
MICCAI
2008
Springer
10 years 9 months ago
MR Brain Tissue Classification Using an Edge-Preserving Spatially Variant Bayesian Mixture Model
In this paper, a spatially constrained mixture model for the segmentation of MR brain images is presented. The novelty of this work is a new, edge preserving, smoothness prior whic...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. ...
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