64 search results - page 8 / 13 » Learning Multiple Latent Variables with Self-Organizing Maps |
KDD
2009
ACM
14 years 9 months ago
2009
ACM
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
ICCV
2005
IEEE
14 years 2 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
2004
13 years 10 months ago
2004
Multiple realizations of continuous-valued time series from a stochastic process often contain systematic variations in rate and amplitude. To leverage the information contained i...
ACCV
2010
Springer
13 years 4 months ago
2010
Springer
Discriminative approaches for human pose estimation model the functional mapping, or conditional distribution, between image features and 3D pose. Learning such multi-modal models ...
NECO
2002
13 years 8 months ago
2002
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...