75 search results - page 4 / 15 » Learning mixture models using a genetic version of the EM al... |
BMCBI
2010
13 years 7 months ago
2010
Background: The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding pro...
PAMI
2008
13 years 7 months ago
2008
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
MVA
2002
13 years 7 months ago
2002
2 Related Works Gaussian mixtures are often used for data modeling in many real-time applications such as video background modeling and speaker direction tracking. The real-time a...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
DATAMINE
2006
13 years 7 months ago
2006
Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of related algorithms l...