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» Semi-Supervised Dimensionality Reduction
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121
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KDD
2003
ACM
127views Data Mining» more  KDD 2003»
16 years 4 months ago
Experiments with random projections for machine learning
Dimensionality reduction via Random Projections has attracted considerable attention in recent years. The approach has interesting theoretical underpinnings and offers computation...
Dmitriy Fradkin, David Madigan
ICASSP
2009
IEEE
15 years 10 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
127
Voted
CIVR
2009
Springer
108views Image Analysis» more  CIVR 2009»
15 years 10 months ago
High-entropy layouts for content-based browsing and retrieval
Multimedia browsing and retrieval systems can use dimensionality reduction methods to map from high-dimensional content-based feature distributions to low-dimensional layout space...
Ruixuan Wang, Stephen J. McKenna, Junwei Han
ICPR
2008
IEEE
15 years 10 months ago
Clustering-based locally linear embedding
The locally linear embedding (LLE) algorithm is considered as a powerful method for the problem of nonlinear dimensionality reduction. In this paper, first, a new method called cl...
Kanghua Hui, Chunheng Wang
141
Voted
COLING
2008
15 years 5 months ago
Using Three Way Data for Word Sense Discrimination
In this paper, an extension of a dimensionality reduction algorithm called NONNEGATIVE MATRIX FACTORIZATION is presented that combines both `bag of words' data and syntactic ...
Tim Van de Cruys