154 search results - page 13 / 31 » Incremental Nonlinear Dimensionality Reduction by Manifold L... |
ICML
2009
IEEE
16 years 14 days ago
2009
IEEE
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
117
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IJCAI
2003
15 years 1 months ago
2003
We equate nonlinear dimensionality reduction (NLDR) to graph embedding with side information about the vertices, and derive a solution to either problem in the form of a kernel-ba...
123
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MICCAI
2007
Springer
16 years 18 days ago
2007
Springer
Abstract. 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 c...
ICML
2007
IEEE
16 years 14 days 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...
118
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CVPR
2007
IEEE
16 years 1 months ago
2007
IEEE
We present an algorithm, Hierarchical ISOmetric SelfOrganizing Map (H-ISOSOM), for a concise, organized manifold representation of complex, non-linear, large scale, high-dimension...