166 search results - page 23 / 34 » Learning a kernel matrix for nonlinear dimensionality reduct... |
CVPR
2008
IEEE
14 years 9 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...
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
The problem of minimizing the rank of a matrix subject to linear equality constraints arises in applications in machine learning, dimensionality reduction, and control theory, and...
ACMACE
2008
ACM
13 years 9 months ago
2008
ACM
Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...