613 search results - page 12 / 123 » Learning the Structure of Linear Latent Variable Models |
147
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AAAI
2012
13 years 4 months ago
2012
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
119
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IFIP12
2004
15 years 3 months ago
2004
Latent class models (LCM) represent the high dimensional data in a smaller dimensional space in terms of latent variables. They are able to automatically discover the patterns from...
122
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CSDA
2010
15 years 1 months ago
2010
We propose a model for a point-referenced spatially correlated ordered categorical response and methodology for estimation of model parameters. Models and methods for spatially co...
122
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DAGM
2010
Springer
15 years 2 months ago
2010
Springer
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
162
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CVPR
2011
IEEE
14 years 5 months ago
2011
IEEE
We propose a novel nonlinear, probabilistic and variational method for adding shape information to level setbased segmentation and tracking. Unlike previous work, we represent sha...