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Dimensionality reduction

Known as: Dimension reduction, Reduction 
In machine learning and statistics, dimensionality reduction or dimension reduction is the process of reducing the number of random variables under… 
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Papers overview

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Highly Cited
2008
Highly Cited
2008
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but… 
Highly Cited
2006
Highly Cited
2006
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that 'similar… 
Review
2006
Review
2006
Dimension reduction techniques were discussed from the two aspects: feature selection and dimension transformation. Firstly, the… 
Review
2006
Review
2006
How can we search for low dimensional structure in high dimensional data? If the data is mainly confined to a low dimensional… 
Highly Cited
2004
Highly Cited
2004
We propose a novel method of dimensionality reduction for supervised learning problems. Given a regression or classification… 
Highly Cited
2001
Highly Cited
2001
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because… 
Highly Cited
2001
Highly Cited
2001
Abstract. The problem of similarity search in large time series databases has attracted much attention recently. It is a non… 
Highly Cited
2000
Highly Cited
2000
Pattern recognition generally requires that objects be described in terms of a set of measurable features. The selection and… 
Highly Cited
2000
Highly Cited
2000
Abstract : We investigate the use of dimensionality reduction to improve performance for a new class of data analysis software… 
Highly Cited
1991
Highly Cited
1991
Abstract Modern advances in computing power have greatly widened scientists' scope in gathering and investigating information…