189 search results - page 7 / 38 » Unsupervised Nonlinear Manifold Learning |
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
MICCAI
2009
Springer
14 years 2 months ago
2009
Springer
This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
NIPS
2004
13 years 9 months ago
2004
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
WSOM
2009
Springer
14 years 2 months ago
2009
Springer
We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-su...
ECCV
2006
Springer
14 years 9 months ago
2006
Springer
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...