74 search results - page 4 / 15 » Nonlinear Manifold Learning for Data Stream |
SDM
2007
SIAM
13 years 8 months ago
2007
SIAM
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
BMVC
2010
13 years 5 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
CVPR
2004
IEEE
14 years 9 months ago
2004
IEEE
We propose methods for outlier handling and noise reduction using weighted local linear smoothing for a set of noisy points sampled from a nonlinear manifold. The methods can be u...
VLSISP
2010
13 years 5 months ago
2010
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
JMLR
2010
13 years 2 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...