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» Multi-Instance Dimensionality Reduction
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ICIP
2006
IEEE
14 years 9 months ago
Wavelet Principal Component Analysis and its Application to Hyperspectral Images
We investigate reducing the dimensionality of image sets by using principal component analysis on wavelet coefficients to maximize edge energy in the reduced dimension images. Lar...
Maya R. Gupta, Nathaniel P. Jacobson
AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
14 years 1 months ago
A Discriminant Analysis for Undersampled Data
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...
Matthew Robards, Junbin Gao, Philip Charlton
SDM
2007
SIAM
126views Data Mining» more  SDM 2007»
13 years 9 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
SDM
2007
SIAM
108views Data Mining» more  SDM 2007»
13 years 9 months ago
Semi-Supervised Dimensionality Reduction
Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
ACMSE
2005
ACM
14 years 1 months ago
Using nonlinear dimensionality reduction in 3D figure animation
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 ...
A. Elizabeth Seward, Bobby Bodenheimer