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CIKM
2003
Springer
13 years 10 months ago
Dimensionality reduction using magnitude and shape approximations
High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
Ümit Y. Ogras, Hakan Ferhatosmanoglu
ICIP
2007
IEEE
14 years 7 months ago
Projection onto a Shape Manifold for Image Segmentation with Prior
Image segmentation with shape priors has received a lot of attention over the past years. Most existing work focuses on a linearized shape space with small deformation modes aroun...
Florent Ségonne, Patrick Etyngier, Renaud K...
CVPR
2004
IEEE
14 years 7 months ago
Fast Contour Matching Using Approximate Earth Mover's Distance
Weighted graph matching is a good way to align a pair of shapes represented by a set of descriptive local features; the set of correspondences produced by the minimum cost matchin...
Kristen Grauman, Trevor Darrell
SODA
2010
ACM
171views Algorithms» more  SODA 2010»
14 years 2 months ago
Coresets and Sketches for High Dimensional Subspace Approximation Problems
We consider the problem of approximating a set P of n points in Rd by a j-dimensional subspace under the p measure, in which we wish to minimize the sum of p distances from each p...
Dan Feldman, Morteza Monemizadeh, Christian Sohler...
SDM
2007
SIAM
126views Data Mining» more  SDM 2007»
13 years 6 months ago
Nonlinear Dimensionality Reduction using Approximate Nearest Neighbors
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...
Erion Plaku, Lydia E. Kavraki