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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… Expand
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Related topics

Related topics

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Apache SparkAutoencoderBackpropagationBias–variance tradeoff
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Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2008
Highly Cited
2008
Transfer Learning via Dimensionality Reduction
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but… Expand
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Highly Cited
2007
Highly Cited
2007
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
A large family of algorithms - supervised or unsupervised; stemming from statistics or geometry theory - has been designed to… Expand
Highly Cited
2006
Highly Cited
2006
Dimensionality Reduction by Learning an Invariant Mapping
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that 'similar… Expand
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Highly Cited
2004
Highly Cited
2004
Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
We propose a novel method of dimensionality reduction for supervised learning problems. Given a regression or classification… Expand
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Review
2002
Review
2002
A Survey of Dimension Reduction Techniques
Advances in data collection and storage capabilities during the past decades have led to an information overload in most sciences… Expand
Highly Cited
2002
Highly Cited
2002
Locally adaptive dimensionality reduction for indexing large time series databases
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because… Expand
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Highly Cited
2001
Highly Cited
2001
Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases
Abstract. The problem of similarity search in large time series databases has attracted much attention recently. It is a non… Expand
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Highly Cited
2000
Highly Cited
2000
Dimensionality reduction using genetic algorithms
Pattern recognition generally requires that objects be described in terms of a set of measurable features. The selection and… Expand
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Highly Cited
2000
Highly Cited
2000
Application of Dimensionality Reduction in Recommender System - A Case Study
Abstract : We investigate the use of dimensionality reduction to improve performance for a new class of data analysis software… Expand
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Highly Cited
1991
Highly Cited
1991
Sliced Inverse Regression for Dimension Reduction
Abstract Modern advances in computing power have greatly widened scientists' scope in gathering and investigating information… Expand
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