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Dimensionality and Its Reduction

Andrew J. Connolly, Jacob T. VanderPlas, Alexander Gray, Andrew J. Connolly, Jacob T. VanderPlas, and Alexander Gray

in Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data

Published in print:
2014
Published Online:
October 2017
ISBN:
9780691151687
eISBN:
9781400848911
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691151687.003.0007
Subject:
Physics, Particle Physics / Astrophysics / Cosmology

With the dramatic increase in data available from a new generation of astronomical telescopes and instruments, many analyses must address the question of the complexity as well as size of the data ... More


Spectral Methods for Dimensionality Reduction

Saul Lawrence K., Weinberger Kilian Q., Sha Fei, Ham Jihun, and Lee Daniel D.

in Semi-Supervised Learning

Published in print:
2006
Published Online:
August 2013
ISBN:
9780262033589
eISBN:
9780262255899
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262033589.003.0016
Subject:
Computer Science, Machine Learning

This chapter provides an overview of unsupervised learning algorithms that can be viewed as spectral methods for linear and nonlinear dimensionality reduction. Spectral methods have recently emerged ... More


Essays in Nonlinear Time Series Econometrics

Niels Haldrup, Mika Meitz, and Pentti Saikkonen (eds)

Published in print:
2014
Published Online:
August 2014
ISBN:
9780199679959
eISBN:
9780191760136
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199679959.001.0001
Subject:
Economics and Finance, Econometrics

This book is a collection of 14 original research articles presented at the conference Nonlinear Time Series Econometrics that was held in Ebeltoft, Denmark, in June 2012. The conference gathered ... More


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