148 search results - page 26 / 30 » Riemannian Manifold Learning for Nonlinear Dimensionality Re... |
WACV
2005
IEEE
13 years 11 months ago
2005
IEEE
Isomap is an exemplar of a set of data driven nonlinear dimensionality reduction techniques that have shown promise for the analysis of images and video. These methods parameteriz...
ECCV
2002
Springer
14 years 7 months ago
2002
Springer
A visual representation of an object must meet at least three basic requirements. First, it must allow identification of the object in the presence of slight but unpredictable chan...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
JMLR
2010
13 years 16 days ago
2010
Given several related learning tasks, we propose a nonparametric Bayesian model that captures task relatedness by assuming that the task parameters (i.e., predictors) share a late...
ISVC
2010
Springer
13 years 4 months ago
2010
Springer
Abstract. We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data. Analyzing the complex 3D motion o...