154 search results - page 8 / 31 » Incremental Nonlinear Dimensionality Reduction by Manifold L... |
104
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NIPS
1997
15 years 1 months ago
1997
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
ICPR
2002
IEEE
16 years 22 days ago
2002
IEEE
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...
CVPR
2007
IEEE
16 years 1 months ago
2007
IEEE
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...
101
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ICCV
2009
IEEE
16 years 4 months ago
2009
IEEE
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
109
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GRC
2008
IEEE
15 years 21 days ago
2008
IEEE
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...