7 search results - page 1 / 2 » On mixture density and maximum likelihood power estimation v... |
NIPS
1998
13 years 6 months ago
1998
We present the CEM (Conditional Expectation Maximization) algorithm as an extension of the EM (Expectation Maximization) algorithm to conditional density estimation under missing ...
ASPDAC
2000
ACM
13 years 10 months ago
2000
ACM
ICIP
2007
IEEE
14 years 7 months ago
2007
IEEE
Gaussian mixture models have been widely used in image segmentation. However, such models are sensitive to outliers. In this paper, we consider a robust model for image segmentati...
CIVR
2006
Springer
13 years 9 months ago
2006
Springer
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
BMEI
2009
IEEE
13 years 6 months ago
2009
IEEE
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...