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INFORMATICALT
2002
136views more  INFORMATICALT 2002»
13 years 7 months ago
Comparison of Poisson Mixture Models for Count Data Clusterization
Abstract. Five methods for count data clusterization based on Poisson mixture models are described. Two of them are parametric, the others are semi-parametric. The methods emlploy ...
Jurgis Susinskas, Marijus Radavicius
GFKL
2005
Springer
141views Data Mining» more  GFKL 2005»
14 years 1 months ago
On External Indices for Mixtures: Validating Mixtures of Genes
Mixture models represent results of gene expression cluster analysis in a more natural way than ’hard’ partitions. This is also true for the representation of gene labels, such...
Ivan G. Costa, Alexander Schliep
BMCBI
2007
138views more  BMCBI 2007»
13 years 8 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
ICIP
2007
IEEE
14 years 10 months ago
Image Denoising with Nonparametric Hidden Markov Trees
We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
AAAI
2007
13 years 10 months ago
Probabilistic Community Discovery Using Hierarchical Latent Gaussian Mixture Model
Complex networks exist in a wide array of diverse domains, ranging from biology, sociology, and computer science. These real-world networks, while disparate in nature, often compr...
Haizheng Zhang, C. Lee Giles, Henry C. Foley, John...