148 search results - page 10 / 30 » Riemannian Manifold Learning for Nonlinear Dimensionality Re... |
ICCV
2007
IEEE
15 years 4 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
15 years 10 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
14 years 11 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
15 years 10 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...
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ICASSP
2008
IEEE
15 years 4 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...