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ECCV
2006
Springer
15 years 11 months ago
Riemannian Manifold Learning for Nonlinear Dimensionality Reduction
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
Tony Lin, Hongbin Zha, Sang Uk Lee
IEEEVAST
2010
14 years 4 months ago
DimStiller: Workflows for dimensional analysis and reduction
DimStiller is a system for dimensionality reduction and analysis. It frames the task of understanding and transforming input dimensions as a series of analysis steps where users t...
Stephen Ingram, Tamara Munzner, Veronika Irvine, M...
CVPR
2005
IEEE
15 years 11 months ago
Rank-R Approximation of Tensors: Using Image-as-Matrix Representation
We present a novel multilinear algebra based approach for reduced dimensionality representation of image ensembles. We treat an image as a matrix, instead of a vector as in tradit...
Hongcheng Wang, Narendra Ahuja
CIARP
2006
Springer
15 years 1 months ago
Automatic Band Selection in Multispectral Images Using Mutual Information-Based Clustering
Feature selection and dimensionality reduction are crucial research fields in pattern recognition. This work presents the application of a novel technique on dimensionality reducti...
Adolfo Martínez Usó, Filiberto Pla, ...
CVPR
2008
IEEE
15 years 11 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