28 search results - page 3 / 6 » Efficient Sampling for Gaussian Process Inference using Cont... |
TSP
2008
13 years 5 months ago
2008
Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fie...
CVPR
2004
IEEE
13 years 9 months ago
2004
IEEE
Graphical models are powerful tools for processing images. However, the large dimensionality of even local image data poses a difficulty: representing the range of possible graphi...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
A mechanism for efficient mean-shift belief propagation (MSBP) is introduced. The novelty of our work is to use mean-shift to perform nonparametric mode-seeking on belief surfaces...
CVPR
2003
IEEE
14 years 7 months ago
2003
IEEE
In many applications of graphical models arising in computer vision, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. There...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...