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» Unsupervised Learning of Finite Mixture Models
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KDD
2004
ACM
237views Data Mining» more  KDD 2004»
14 years 5 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
ICPR
2000
IEEE
14 years 6 months ago
Unsupervised Selection and Estimation of Finite Mixture Models
We propose a new method for fitting mixture models that performs component selection and does not require external initialization. The novelty of our approach includes: a minimum ...
Anil K. Jain, Mário A. T. Figueiredo
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 6 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
IWANN
2005
Springer
13 years 11 months ago
Manifold Constrained Finite Gaussian Mixtures
In many practical applications, the data is organized along a manifold of lower dimension than the dimension of the embedding space. This additional information can be used when le...
Cédric Archambeau, Michel Verleysen
ICIP
2005
IEEE
14 years 7 months ago
SAR images as mixtures of Gaussian mixtures
We consider the problem of image segmentation by clustering local histograms with parametric mixture-of-mixture models. These models represent each cluster by a single mixture mod...
Peter Orbanz, Joachim M. Buhmann