148 search results - page 10 / 30 » Riemannian Manifold Learning for Nonlinear Dimensionality Re... |
ICCV
2007
IEEE
14 years 1 months ago
2007
IEEE
We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a category o...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
The problem of nonlinear dimensionality reduction is considered. We focus on problems where prior information is available, namely, semi-supervised dimensionality reduction. It is...
NIPS
2004
13 years 9 months ago
2004
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
KDD
2007
ACM
14 years 8 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
This paper presents a new approach to feature analysis in automatic speech recognition (ASR) based on locality preserving projections (LPP). LPP is a manifold based dimensionality...