613 search results - page 23 / 123 » Learning the Structure of Linear Latent Variable Models |
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
NAACL
2010
13 years 5 months ago
2010
We describe a class of translation model in which a set of input variants encoded as a context-free forest is translated using a finitestate translation model. The forest structur...
ICTAI
2009
IEEE
14 years 2 months ago
2009
IEEE
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
NIPS
2008
13 years 9 months ago
2008
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
ICIP
2007
IEEE
14 years 9 months ago
2007
IEEE
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...