765 search results - page 8 / 153 » Learning from Multiple Annotators with Gaussian Processes |
PAMI
2008
13 years 6 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...
CVPR
2006
IEEE
14 years 8 months ago
2006
IEEE
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
ECML
2006
Springer
13 years 10 months ago
2006
Springer
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
CSB
2005
IEEE
14 years 10 days ago
2005
IEEE
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
ICML
2004
IEEE
14 years 4 days ago
2004
IEEE
This paper describes an e cient method for learning the parameters of a Gaussian process (GP). The parameters are learned from multiple tasks which are assumed to have been drawn ...