785 search results - page 9 / 157 » Semi-Supervised Dimensionality Reduction |
AUSDM
2007
Springer
15 years 3 months ago
2007
Springer
One of the inherent problems in pattern recognition is the undersampled data problem, also known as the curse of dimensionality reduction. In this paper a new algorithm called pai...
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SDM
2007
SIAM
14 years 11 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...
ACMSE
2005
ACM
15 years 3 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 ...
ICML
2005
IEEE
15 years 10 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...
AAAI
2010
14 years 11 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 ...