509 search results - page 58 / 102 » Using Learning for Approximation in Stochastic Processes |
132
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NIPS
2000
15 years 3 months ago
2000
People can understand complex auditory and visual information, often using one to disambiguate the other. Automated analysis, even at a lowlevel, faces severe challenges, includin...
126
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ECCV
2008
Springer
16 years 4 months ago
2008
Springer
We present a new Gaussian Process inference algorithm, called Online Sparse Matrix Gaussian Processes (OSMGP), and demonstrate its merits with a few vision applications. The OSMGP ...
117
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CEC
2005
IEEE
15 years 8 months ago
2005
IEEE
This paper presents a study on Hierarchical Surrogate-Assisted Evolutionary Algorithm (HSAEA) using different global surrogate models for solving computationally expensive optimiza...
124
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CMSB
2007
Springer
15 years 8 months ago
2007
Springer
We explore some presynaptic mechanisms of the calyx of Held synapse through a stochastic model. The model, drawn from a kinetic approach developed in literature, exploits process c...
130
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DSMML
2004
Springer
15 years 7 months ago
2004
Springer
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...