791 search results - page 11 / 159 » Non-Linear Dimensionality Reduction |
179
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SDM
2007
SIAM
15 years 5 months ago
2007
SIAM
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
143
Voted
SDM
2007
SIAM
15 years 5 months ago
2007
SIAM
Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
126
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ACMSE
2005
ACM
15 years 9 months ago
2005
ACM
This paper explores a method for re-sequencing an existing set of animation, specifically motion capture data, to generate new motion. Re-using animation is helpful in designing ...
183
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ICML
2005
IEEE
16 years 4 months ago
2005
IEEE
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
135
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AAAI
2010
15 years 5 months ago
2010
Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...