Random projection

Known as: Gaussian random projection 
In mathematics and statistics, random projection is a technique used to reduce the dimensionality of a set of points which lie in Euclidean space… (More)
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Highly Cited
2013
Highly Cited
2013
Random projection algorithm is of interest for constrained optimization when the constraint set is not known in advance or the… (More)
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Highly Cited
2009
Highly Cited
2009
Many types of data and information can be described by concise models that suggest each data vector (or signal) actually has “few… (More)
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Highly Cited
2008
Highly Cited
2008
We present a simple variant of the k-d tree which automatically adapts to intrinsic low dimensional structure in data without… (More)
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Highly Cited
2007
Highly Cited
2007
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M… (More)
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Highly Cited
2006
Highly Cited
2006
Recent results show that a relatively small number of random projections of a signal can contain most of its salient information… (More)
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Highly Cited
2006
Highly Cited
2006
This paper explores the possibility of using multiplicative random projection matrices for privacy preserving distributed data… (More)
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Highly Cited
2003
Highly Cited
2003
We investigate how random projection can best be used for clustering high dimensional data. Random projection has been shown to… (More)
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Highly Cited
2001
Highly Cited
2001
Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the… (More)
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Highly Cited
2001
Highly Cited
2001
A classic result of Johnson and Lindenstrauss asserts that any set of n points in d-dimensional Euclidean space can be embedded… (More)
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Highly Cited
2000
Highly Cited
2000
Recent theoretical work has identified random projection as a promising dimensionality reduction technique for learning mixtures… (More)
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