88 search results - page 7 / 18 » Distance Preserving Dimension Reduction for Manifold Learnin... |
151
Voted
IDEAL
2010
Springer
15 years 2 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 ...
198
Voted
JMLR
2010
14 years 10 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...
150
Voted
NIPS
2007
15 years 5 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...
157
Voted
AMDO
2006
Springer
15 years 7 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...
155
Voted
CVPR
2010
IEEE
15 years 10 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...