785 search results - page 26 / 157 » Semi-Supervised Dimensionality Reduction |
137
Voted
ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
128
Voted
CVPR
2008
IEEE
16 years 5 months ago
2008
IEEE
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
130
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ICML
2007
IEEE
16 years 4 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...
152
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ICML
2006
IEEE
16 years 4 months ago
2006
IEEE
We present a unified duality view of several recently emerged spectral methods for nonlinear dimensionality reduction, including Isomap, locally linear embedding, Laplacian eigenm...
113
Voted
ICASSP
2008
IEEE
15 years 10 months ago
2008
IEEE
Dimensionality reduction (DR) is a major issue to improve the efficiency of the classifiers in Hyperspectral images (HSI). Recently, the independent component analysis (ICA) app...