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» Learning Probabilistic Models of Relational Structure
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AAAI
2011
14 years 18 days ago
Incorporating Boosted Regression Trees into Ecological Latent Variable Models
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Diet...
125
Voted
IROS
2009
IEEE
145views Robotics» more  IROS 2009»
15 years 7 months ago
Utilizing prior information to enhance self-supervised aerial image analysis for extracting parking lot structures
Abstract— Road network information (RNI) simplifies autonomous driving by providing strong priors about driving environments. Its usefulness has been demonstrated in the DARPA U...
Young-Woo Seo, Chris Urmson
MICCAI
1998
Springer
15 years 4 months ago
Multi-object Deformable Templates Dedicated to the Segmentation of Brain Deep Structures
We propose a new way of embedding shape distributions in a topological deformable template. These distributions rely on global shape descriptors corresponding to the 3D moment inva...
Fabrice Poupon, Jean-Francois Mangin, Dominique Ha...
IEEEICCI
2009
IEEE
14 years 10 months ago
Learning from an ensemble of Receptive Fields
Abstract-In this paper, we construct a neural-inspired computational model based on the representational capabilities of receptive fields. The proposed model, known as Shape Encodi...
Hanlin Goh, Joo Hwe Lim, Chai Quek
107
Voted
ICML
2007
IEEE
16 years 1 months ago
Unsupervised estimation for noisy-channel models
Shannon's Noisy-Channel model, which describes how a corrupted message might be reconstructed, has been the corner stone for much work in statistical language and speech proc...
Markos Mylonakis, Khalil Sima'an, Rebecca Hwa