766 search results - page 14 / 154 » Gaussian Process Models of Spatial Aggregation Algorithms |
NIPS
2007
13 years 9 months ago
2007
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
PAMI
2010
13 years 6 months ago
2010
—We present a generative model and inference algorithm for 3D nonrigid object tracking. The model, which we call G-flow, enables the joint inference of 3D position, orientation, ...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
In this paper we propose a new segmentation algorithm which combines patch-based information with edge cues under a probabilistic framework. We use a mixture of multiple Gaussians...
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....