60 search results - page 4 / 12 » Continuous nonlinear dimensionality reduction by kernel Eige... |
ICML
2004
IEEE
13 years 11 months ago
2004
IEEE
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
NIPS
2007
13 years 7 months ago
2007
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
We present a unified duality view of several recently emerged spectral methods for nonlinear dimensionality reduction, including Isomap, locally linear embedding, Laplacian eigenm...
ICIP
2005
IEEE
14 years 7 months ago
2005
IEEE
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
This paper examines the problem of extracting lowdimensional manifold structure given millions of highdimensional face images. Specifically, we address the computational challenge...