474 search results - page 25 / 95 » Bayesian Feature and Model Selection for Gaussian Mixture Mo... |
147
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ICASSP
2011
IEEE
14 years 7 months ago
2011
IEEE
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
161
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MICCAI
2005
Springer
16 years 4 months ago
2005
Springer
We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
104
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UAI
2004
15 years 5 months ago
2004
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
134
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CDC
2008
IEEE
15 years 10 months ago
2008
IEEE
— The goal of this paper is to develop modeling techniques for complex systems for the purposes of control, estimation, and inference: (i) A new class of Hidden Markov Models is ...
139
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ECCV
2008
Springer
16 years 5 months ago
2008
Springer
An approach to the analysis of images of regular texture is proposed in which lattice hypotheses are used to define statistical models. These models are then compared in terms of t...