270 search results - page 6 / 54 » Hierarchical Gaussian process latent variable models |
112
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ICONIP
2007
14 years 11 months ago
2007
Abstract. An effective way to examine causality is to conduct an experiment with random assignment. However, in many cases it is impossible or too expensive to perform controlled ...
120
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CVPR
2011
IEEE
14 years 1 months ago
2011
IEEE
We propose a novel nonlinear, probabilistic and variational method for adding shape information to level setbased segmentation and tracking. Unlike previous work, we represent sha...
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
ICASSP
2008
IEEE
15 years 4 months ago
2008
IEEE
In this paper we propose novel algorithms for image restoration and parameter estimation with a Generalized Gaussian Markov Random Field prior utilizing variational distribution a...
NIPS
2008
14 years 11 months ago
2008
We present a sparse approximation approach for dependent output Gaussian processes (GP). Employing a latent function framework, we apply the convolution process formalism to estab...