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125
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ICCS
2005
Springer
15 years 10 months ago
2005
Springer
We present a new framework for robust 3D tracking, using a dynamic data driven coupling of continuous and discrete methods to overcome their limitations. Our method uses primarily ...
158
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AAAI
2011
14 years 4 months ago
2011
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
166
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ALT
2006
Springer
16 years 1 months ago
2006
Springer
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
221
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CVPR
2009
IEEE
17 years 4 days ago
2009
IEEE
Given an image, we propose a hierarchical generative
model that classifies the overall scene, recognizes and segments
each object component, as well as annotates the image
with ...
142
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ICML
2006
IEEE
16 years 5 months ago
2006
IEEE
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...