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» Density Estimation Using Mixtures of Mixtures of Gaussians
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ICASSP
2011
IEEE
13 years 1 months ago
Blind separation of multiple binary sources from one nonlinear mixture
We propose a new method for the blind separation of multiple binary signals from a single general nonlinear mixture. In addition to the usual independence assumption on the input ...
Konstantinos I. Diamantaras, Theophilos Papadimitr...
TIP
2002
98views more  TIP 2002»
13 years 9 months ago
Joint-MAP Bayesian tomographic reconstruction with a gamma-mixture prior
We address the problem of Bayesian image reconstruction with a prior that captures the notion of a clustered intensity histogram. The problem is formulated in the framework of a j...
Ing-Tsung Hsiao, Anand Rangarajan, Gene Gindi
CSDA
2010
111views more  CSDA 2010»
13 years 9 months ago
Mixtures of regressions with predictor-dependent mixing proportions
We extend the standard mixture of linear regressions model by allowing mixing proportions to be modeled nonparametrically as a function of the predictors. This framework allows fo...
D. S. Young, D. R. Hunter
WABI
2009
Springer
124views Bioinformatics» more  WABI 2009»
14 years 3 months ago
Mimosa: Mixture Model of Co-expression to Detect Modulators of Regulatory Interaction
Background: Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often use...
Matthew Hansen, Logan Everett, Larry Singh, Sridha...
ICASSP
2011
IEEE
13 years 1 months ago
How efficient is estimation with missing data?
In this paper, we present a new evaluation approach for missing data techniques (MDTs) where the efficiency of those are investigated using listwise deletion method as reference....
Seliz G. Karadogan, Letizia Marchegiani, Lars Kai ...