132 search results - page 21 / 27 » Context-specific approximation in probabilistic inference |
89
Voted
PAMI
2006
15 years 8 days ago
2006
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
112
Voted
ECCV
2004
Springer
16 years 2 months ago
2004
Springer
We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
116
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CVPR
2008
IEEE
15 years 2 months ago
2008
IEEE
In photometric stereo a robust method is required to deal with outliers, such as shadows and non-Lambertian reflections. In this paper we rely on a probabilistic imaging model tha...
112
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ICML
2010
IEEE
15 years 1 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...
132
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MMAS
2011
Springer
14 years 7 months ago
2011
Springer
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...