509 search results - page 76 / 102 » Using Learning for Approximation in Stochastic Processes |
NIPS
2008
13 years 11 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
ATAL
2005
Springer
14 years 3 months ago
2005
Springer
Robust sequence prediction is an essential component of an intelligent agent acting in a dynamic world. We consider the case of near-future event prediction by an online learning ...
IJCV
2007
13 years 9 months ago
2007
Abstract. Inspired by the early visual system of many mammalians we consider the construction of-and reconstruction from- an orientation score Uf : R2 ×S1 → C as a local orienta...
WSC
1998
13 years 11 months ago
1998
Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or...
ECCV
2002
Springer
14 years 11 months ago
2002
Springer
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...