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» Unsupervised Learning of Finite Mixture Models
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KDD
2004
ACM
237views Data Mining» more  KDD 2004»
15 years 10 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
15 years 10 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»
14 years 11 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
15 years 3 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
15 years 11 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