88 search results - page 15 / 18 » Distance Preserving Dimension Reduction for Manifold Learnin... |
DEXA
2006
Springer
15 years 3 months ago
2006
Springer
Abstract. Nearest neighbor search has a wide variety of applications. Unfortunately, the majority of search methods do not scale well with dimensionality. Recent efforts have been ...
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AI
2011
Springer
14 years 3 months ago
2011
Springer
Abstract. Subspace mapping methods aim at projecting high-dimensional data into a subspace where a specific objective function is optimized. Such dimension reduction allows the re...
CGF
2010
14 years 11 months ago
2010
A common operation in many geometry processing algorithms consists of finding correspondences between pairs of shapes by finding structure-preserving maps between them. A particul...
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CVPR
2007
IEEE
16 years 1 months ago
2007
IEEE
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
NIPS
2008
15 years 1 months ago
2008
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...