219 search results - page 18 / 44 » Learning the Dimensionality of Hidden Variables |
ESWA
2006
14 years 11 months ago
2006
Gene networks describe functional pathways in a given cell or tissue, representing processes such as metabolism, gene expression regulation, and protein or RNA transport. Thus, le...
100
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ICML
2000
IEEE
16 years 16 days ago
2000
IEEE
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
138
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CVPR
2011
IEEE
14 years 3 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...
107
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ICML
2008
IEEE
16 years 16 days ago
2008
IEEE
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
NIPS
2001
15 years 1 months ago
2001
Estimating insurance premia from data is a difficult regression problem for several reasons: the large number of variables, many of which are discrete, and the very peculiar shape...