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» Dimensionality reduction by unsupervised regression
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ICIP
2007
IEEE
13 years 9 months ago
Unsupervised Nonlinear Manifold Learning
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...
BMVC
2010
13 years 3 months ago
Histogram of Body Poses and Spectral Regression Discriminant Analysis for Human Action Categorization
This paper explores a recently proposed and rarely reported subspace learning method, Spectral Regression Discriminant Analysis (SRDA) [1, 2], on silhouette based human action rec...
Ling Shao, Xiuli Chen
IJPRAI
2010
109views more  IJPRAI 2010»
13 years 2 months ago
Disguised Discrimination of Locality-Based Unsupervised Dimensionality Reduction
: Many locality-based unsupervised dimensionality reduction (DR) algorithms have recently been proposed and demonstrated to be effective to a certain degree in some classification ...
Bo Yang, Songcan Chen
ICPR
2010
IEEE
13 years 7 months ago
Temporal Extension of Laplacian Eigenmaps for Unsupervised Dimensionality Reduction of Time Series
—A novel non-linear dimensionality reduction method, called Temporal Laplacian Eigenmaps, is introduced to process efficiently time series data. In this embedded-based approach,...
Michal Lewandowski, Jesus Martinez-Del-Rincon, Dim...
CVPR
2008
IEEE
14 years 7 months ago
Dimensionality reduction using covariance operator inverse regression
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
Minyoung Kim, Vladimir Pavlovic