141 search results - page 15 / 29 » Grouping and dimensionality reduction by locally linear embe... |
SDM
2009
SIAM
14 years 6 months ago
2009
SIAM
Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
ICMCS
2005
IEEE
14 years 2 months ago
2005
IEEE
Semi-definite Embedding (SDE) has been a recently proposed to maximize the sum of pair wise squared distances between outputs while the input data and outputs are locally isometri...
ICCV
2007
IEEE
14 years 3 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
AMFG
2003
IEEE
14 years 2 months ago
2003
IEEE
In this paper, we propose the concept of Manifold of Facial Expression based on the observation that images of a subject’s facial expressions define a smooth manifold in the hig...
NIPS
2003
13 years 10 months ago
2003
Spectral methods for nonlinear dimensionality reduction (NLDR) impose a neighborhood graph on point data and compute eigenfunctions of a quadratic form generated from the graph. W...