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» Dimensionality Reduction of Clustered Data Sets
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IEEEMM
2007
146views more  IEEEMM 2007»
13 years 8 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
ACST
2006
13 years 10 months ago
Distributed hierarchical document clustering
This paper investigates the applicability of distributed clustering technique, called RACHET [1], to organize large sets of distributed text data. Although the authors of RACHET c...
Debzani Deb, M. Muztaba Fuad, Rafal A. Angryk
IJCV
2008
155views more  IJCV 2008»
13 years 8 months ago
Fast Transformation-Invariant Component Analysis
For software and more illustrations: http://www.psi.utoronto.ca/anitha/fastTCA.htm Dimensionality reduction techniques such as principal component analysis and factor analysis are...
Anitha Kannan, Nebojsa Jojic, Brendan J. Frey
ICASSP
2009
IEEE
14 years 3 months ago
Separable PCA for image classification
As an alternative to standard PCA, matrix-based image dimensionality reduction methods have recently been proposed and have gained attention due to reported computational efficie...
Yongxin Taylor Xi, Peter J. Ramadge
NIPS
1997
13 years 10 months ago
Mapping a Manifold of Perceptual Observations
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
Joshua B. Tenenbaum