137 search results - page 2 / 28 » Ordinal Embedding: Approximation Algorithms and Dimensionali... |
SDM
2007
SIAM
13 years 6 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...
ICPR
2000
IEEE
13 years 9 months ago
2000
IEEE
For many pattern recognition methods, high recognition accuracy is obtained at very high expense of computational cost. In this paper, a new algorithm that reduces the computation...
ICML
2005
IEEE
14 years 6 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...
CVPR
2005
IEEE
14 years 7 months ago
2005
IEEE
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
TSMC
2010
12 years 12 months ago
2010
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...