177 search results - page 7 / 36 » Sparse Representation for Gaussian Process Models |
NIPS
2001
13 years 9 months ago
2001
The adaptive TAP Gibbs free energy for a general densely connected probabilistic model with quadratic interactions and arbritary single site constraints is derived. We show how a ...
PKDD
2010
Springer
13 years 6 months ago
2010
Springer
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
ICIP
2004
IEEE
14 years 9 months ago
2004
IEEE
We propose a mixture of multiple linear models, also known as hybrid linear model, for a sparse representation of an image. This is a generalization of the conventional KarhunenLo...
JMLR
2002
13 years 7 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
PAMI
2008
13 years 7 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...