88 search results - page 9 / 18 » Distance Preserving Dimension Reduction for Manifold Learnin... |
110
Voted
ICML
2006
IEEE
16 years 2 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...
104
Voted
IJCAI
2007
15 years 3 months ago
2007
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
160
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MM
2004
ACM
15 years 7 months ago
2004
ACM
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
106
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ICML
2007
IEEE
16 years 2 months ago
2007
IEEE
This paper proposes a new map building framework for mobile robot named Localization-Free Mapping by Dimensionality Reduction (LFMDR). In this framework, the robot map building is...
107
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ICPR
2008
IEEE
15 years 8 months ago
2008
IEEE
We propose a new method to retrieve similar face images from large face databases. The proposed method extracts a set of Haar-like features, and integrates these features with sup...