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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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Related topics
Related topics
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Apache Spark
Autoencoder
Backpropagation
Bias–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
Sinno Jialin Pan
,
James T. Kwok
,
Qiang Yang
AAAI Conference on Artificial Intelligence
2008
Corpus ID: 6953522
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but…
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Highly Cited
2006
Highly Cited
2006
Dimensionality Reduction by Learning an Invariant Mapping
R. Hadsell
,
S. Chopra
,
Yann LeCun
Computer Vision and Pattern Recognition
2006
Corpus ID: 8281592
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that 'similar…
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Review
2006
Review
2006
Survey on dimension reduction techniques
Minghe Xu
2006
Corpus ID: 124428234
Dimension reduction techniques were discussed from the two aspects: feature selection and dimension transformation. Firstly, the…
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Review
2006
Review
2006
Spectral Methods for Dimensionality Reduction
L. Saul
,
Kilian Q. Weinberger
,
Fei Sha
,
Jihun Ham
,
Daniel D. Lee
Semi-Supervised Learning
2006
Corpus ID: 117033125
How can we search for low dimensional structure in high dimensional data? If the data is mainly confined to a low dimensional…
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Highly Cited
2004
Highly Cited
2004
Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
K. Fukumizu
,
F. Bach
,
Michael I. Jordan
Journal of machine learning research
2004
Corpus ID: 7642935
We propose a novel method of dimensionality reduction for supervised learning problems. Given a regression or classification…
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Highly Cited
2001
Highly Cited
2001
Locally adaptive dimensionality reduction for indexing large time series databases
K. Chakrabarti
,
Eamonn J. Keogh
,
S. Mehrotra
,
M. Pazzani
ACM SIGMOD Conference
2001
Corpus ID: 15192608
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because…
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Highly Cited
2001
Highly Cited
2001
Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases
Eamonn J. Keogh
,
K. Chakrabarti
,
M. Pazzani
,
S. Mehrotra
Knowledge and Information Systems
2001
Corpus ID: 15462747
Abstract. The problem of similarity search in large time series databases has attracted much attention recently. It is a non…
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Highly Cited
2000
Highly Cited
2000
Dimensionality reduction using genetic algorithms
M. Raymer
,
W. Punch
,
E. Goodman
,
L. Kuhn
,
Anil K. Jain
IEEE Transactions on Evolutionary Computation
2000
Corpus ID: 8533646
Pattern recognition generally requires that objects be described in terms of a set of measurable features. The selection and…
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Highly Cited
2000
Highly Cited
2000
Application of Dimensionality Reduction in Recommender System - A Case Study
B. Sarwar
,
G. Karypis
,
J. Konstan
,
J. Riedl
2000
Corpus ID: 17065558
Abstract : We investigate the use of dimensionality reduction to improve performance for a new class of data analysis software…
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Highly Cited
1991
Highly Cited
1991
Sliced Inverse Regression for Dimension Reduction
Ker-Chau Li
1991
Corpus ID: 30158078
Abstract Modern advances in computing power have greatly widened scientists' scope in gathering and investigating information…
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