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» Semi-Supervised Learning of Mixture Models
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ICPR
2008
IEEE
16 years 3 months ago
Component-wise parameter smoothing for learning mixture models
In this paper, we propose a novel component-wise smoothing algorithm that constructs a hierarchy (or family) of smoothened log-likelihood surfaces. Our approach first smoothens th...
Bala Rajaratnam, Chandan K. Reddy
96
Voted
IDA
2010
Springer
15 years 1 months ago
Relevant subtask learning by constrained mixture models
Jaakko Peltonen, Yusuf Yaslan, Samuel Kaski
120
Voted
FGCN
2008
IEEE
155views Communications» more  FGCN 2008»
15 years 4 months ago
Modeling the Marginal Distribution of Gene Expression with Mixture Models
We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
Edward Wijaya, Hajime Harada, Paul Horton
TNN
2010
216views Management» more  TNN 2010»
14 years 9 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok