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Statistical Analysis for High-Dimensional Data: The Abel Symposium 2014 (Abel Symposia)


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ISBN 10: 3319270974 / ISBN 13: 9783319270975
Published by Springer, 2016
Condition: Good Hardcover
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Bibliographic Details

Title: Statistical Analysis for High-Dimensional ...

Publisher: Springer

Publication Date: 2016

Binding: Hardcover

Book Condition:Good

Edition: 1st ed. 2016.

About this title


This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014.

The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection.

Highlighting cutting-edge research and casting light on future research directions, the contributions will benefit graduate students and researchers in computational biology, statistics and the machine learning community.

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