7 search results - page 1 / 2 » Deterministic Latent Variable Models and Their Pitfalls |
SDM
2008
SIAM
13 years 6 months ago
2008
SIAM
We derive a number of well known deterministic latent variable models such as PCA, ICA, EPCA, NMF and PLSA as variational EM approximations with point posteriors. We show that the...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
ICCV
2005
IEEE
13 years 10 months ago
2005
IEEE
We advocate the use of Scaled Gaussian Process Latent Variable Models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a...
NIPS
1996
13 years 5 months ago
1996
Real-valued random hidden variables can be useful for modelling latent structure that explains correlations among observed variables. I propose a simple unit that adds zero-mean G...
PKDD
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. This article presents a method for training Dynamic Factor Graphs (DFG) with continuous latent state variables. A DFG includes factors modeling joint probabilities betwee...