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» Dimensionality Reduction for Classification
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ECCV
2004
Springer
16 years 5 months ago
Transformation-Invariant Embedding for Image Analysis
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
Ali Ghodsi, Jiayuan Huang, Dale Schuurmans
ICML
2008
IEEE
16 years 4 months ago
Manifold alignment using Procrustes analysis
In this paper we introduce a novel approach to manifold alignment, based on Procrustes analysis. Our approach differs from "semisupervised alignment" in that it results ...
Chang Wang, Sridhar Mahadevan
118
Voted
KDD
2003
ACM
127views Data Mining» more  KDD 2003»
16 years 3 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
CIVR
2009
Springer
108views Image Analysis» more  CIVR 2009»
15 years 9 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
COLING
2008
15 years 4 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