922 search results - page 18 / 185 » Learning Gaussian Process Models from Uncertain Data |
BMCBI
2007
13 years 7 months ago
2007
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
ICCV
2007
IEEE
14 years 9 months ago
2007
IEEE
In this paper, we present a tracking framework for capturing articulated human motions in real-time, without the need for attaching markers onto the subject's body. This is a...
UAI
2008
13 years 8 months ago
2008
Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3 ) scaling in computational time to O(nm2 ). Thus far, wo...
ICCV
2005
IEEE
14 years 28 days 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...
FOCS
1999
IEEE
13 years 11 months ago
1999
IEEE
Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with w...