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» Learning the Structure of Linear Latent Variable Models
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AAAI
2012
11 years 10 months ago
A Search Algorithm for Latent Variable Models with Unbounded Domains
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...
Michael Chiang, David Poole
IFIP12
2004
13 years 8 months ago
Introducing a Star Topology into Latent Class Models for Collaborative Filtering
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...
Gabriela Polcicova, Peter Tiño
CSDA
2010
194views more  CSDA 2010»
13 years 7 months ago
A clipped latent variable model for spatially correlated ordered categorical data
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...
Megan Dailey Higgs, Jennifer A. Hoeting
DAGM
2010
Springer
13 years 8 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
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...
Hannes Nickisch, Carl Edward Rasmussen
CVPR
2011
IEEE
12 years 11 months ago
Nonlinear Shape Manifolds as Shape Priors in Level Set Segmentation and Tracking
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...
Victor Prisacariu, Ian Reid