88 search results - page 2 / 18 » Distance Preserving Dimension Reduction for Manifold Learnin... |
ECCV
2008
Springer
14 years 7 months ago
2008
Springer
Head pose estimation is an important task for many face analysis applications, such as face recognition systems and human computer interactions. In this paper we aim to address the...
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 ...
AMR
2007
Springer
13 years 11 months ago
2007
Springer
Distance measures, along with shape features, are the most critical components in a shape-based 3D model retrieval system. Given a shape feature, an optimal distance measure will v...
ICIC
2005
Springer
13 years 11 months ago
2005
Springer
Dimension reduction is a crucial step for pattern recognition and information retrieval tasks to overcome the curse of dimensionality. In this paper a novel unsupervised linear dim...
NIPS
2008
13 years 6 months ago
2008
We study the convergence and the rate of convergence of a local manifold learning algorithm: LTSA [13]. The main technical tool is the perturbation analysis on the linear invarian...