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KDD
2007
ACM
124views Data Mining» more  KDD 2007»
15 years 3 months ago
Hierarchical mixture models: a probabilistic analysis
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Mark Sandler
PRL
2000
58views more  PRL 2000»
14 years 9 months ago
Learning mixture models using a genetic version of the EM algorithm
The need to
Aleix M. Martínez, Jordi Vitrià
ICIP
2000
IEEE
15 years 2 months ago
Modelling Profiles with a Mixture of Gaussians
Point Distribution Models are useful tools for modelling the variability of particular classes of shapes. A common approach is to apply a Principle Component Analysis to the data,...
James Orwell, Darrel Greenhill, Jonathan D. Rymel,...
ICA
2004
Springer
15 years 3 months ago
Blind Maximum Likelihood Separation of a Linear-Quadratic Mixture
Abstract. We proposed recently a new method for separating linearquadratic mixtures of independent real sources, based on parametric identification of a recurrent separating struc...
Shahram Hosseini, Yannick Deville
INFOCOM
2009
IEEE
15 years 4 months ago
Robust Event Boundary Detection in Sensor Networks - A Mixture Model Based Approach
—Detecting event frontline or boundary sensors in a complex sensor network environment is one of the critical problems for sensor network applications. In this paper, we propose ...
Min Ding, Xiuzhen Cheng