88 search results - page 7 / 18 » Distance Preserving Dimension Reduction for Manifold Learnin... |
IDEAL
2010
Springer
13 years 8 months ago
2010
Springer
Dimension reduction for regression (DRR) deals with the problem of finding for high-dimensional data such low-dimensional representations, which preserve the ability to predict a ...
JMLR
2010
13 years 4 months ago
2010
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
NIPS
2007
13 years 11 months ago
2007
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
AMDO
2006
Springer
14 years 1 months ago
2006
Springer
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
43
Voted
CVPR
2010
IEEE
14 years 4 months ago
2010
IEEE
Local features have proven very useful for recognition.
Manifold learning has proven to be a very powerful tool in
data analysis. However, manifold learning application for
imag...