# Nonlinear dimensionality reduction

## Papers overview

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Highly Cited

2014

Highly Cited

2014

- MLSDA@PRICAI
- 2014

This paper proposes to use autoencoders with nonlinear dimensionality reduction in the anomaly detection task. The authors applyâ€¦Â (More)

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Highly Cited

2010

Highly Cited

2010

- Journal of Machine Learning Research
- 2010

Nonlinear dimensionality reduction methods are often used to visualize high-dimensional data, although the existing methods haveâ€¦Â (More)

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Highly Cited

2006

Highly Cited

2006

- IEEE Transactions on Pattern Analysis and Machineâ€¦
- 2006

Understanding the structure of multidimensional patterns, especially in unsupervised cases, is of fundamental importance in dataâ€¦Â (More)

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Highly Cited

2005

Highly Cited

2005

- IEEE Transactions on Systems, Man, andâ€¦
- 2005

When performing visualization and classification, people often confront the problem of dimensionality reduction. Isomap is one ofâ€¦Â (More)

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Highly Cited

2005

Highly Cited

2005

- AISTATS
- 2005

We describe an algorithm for nonlinear dimensionality reduction based on semidefinite programming and kernel matrix factorizationâ€¦Â (More)

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Highly Cited

2004

Highly Cited

2004

- ICML
- 2004

We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Notingâ€¦Â (More)

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Highly Cited

2004

Highly Cited

2004

- SIAM J. Scientific Computing
- 2004

We present a new algorithm for manifold learning and nonlinear dimensionality reduction. Based on a set of unorganized dataâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

- NIPS
- 2002

Recently proposed algorithms for nonlinear dimensionality reduction fall broadly into two categories which have differentâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

- Neural Computation
- 2002

One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complexâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

- IDEAL
- 2002

Nonlinear manifold learning from unorganized data points is a very challenging unsupervised learning and data visualizationâ€¦Â (More)

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