11 search results - page 2 / 3 » Graphical Gaussian modelling of multivariate time series wit... |
PAMI
2008
13 years 5 months ago
2008
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
AINA
2008
IEEE
13 years 11 months ago
2008
IEEE
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
CVPR
2003
IEEE
14 years 7 months ago
2003
IEEE
Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
ESANN
2006
13 years 6 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
JMS
2010
13 years 3 months ago
2010
This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes ...