Isbn: 9783319270975 - statistical analysis for high-dimensional data: the abel symposium 2014: 11 (abel symposia, 11) (8 resultados)

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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvågar, Lofoten, Norway, in May 2014.The focus of the symposium was on statisticaland machine learning methodologies specifically developed for inference in 'bigdata' situations, with particular reference to genomic applications. Thecontributors, who are among the most prominent researchers on the theory ofstatistics for high dimensional inference, present new theories and methods, aswell as challenging applications and computational solutions. Specific themesinclude, among others, variable selection and screening, penalised regressionsparsity, thresholding, low dimensional structures, computational challengesnon-convex situations, learning graphical models, sparse covariance andprecision matrices, semi- and non-parametric formulations, multiple testingclassification, factor models, clustering, and preselection.Highlighting cutting-edge researchand casting light on future research directions, the contributions will benefitgraduate students and researchers in computational biology, statistics and themachine learning community. 320 pp. Englisch.…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvågar, Lofoten, Norway, in May 2014.The focus of the symposium was on statisticaland machine learning methodologies specifically developed for inference in ¿bigdatä situations, with particular reference to genomic applications. Thecontributors, who are among the most prominent researchers on the theory ofstatistics for high dimensional inference, present new theories and methods, aswell as challenging applications and computational solutions. Specific themesinclude, among others, variable selection and screening, penalised regressionsparsity, thresholding, low dimensional structures, computational challengesnon-convex situations, learning graphical models, sparse covariance andprecision matrices, semi- and non-parametric formulations, multiple testingclassification, factor models, clustering, and preselection.Highlighting cutting-edge researchand casting light on future research directions, the contributions will benefitgraduate students and researchers in computational biology, statistics and themachine learning community.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 320 pp. Englisch.…

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvågar, Lofoten, Norway, in May 2014.The focus of the symposium was on statisticaland machine learning methodologies specifically developed for inference in 'bigdata' situations, with particular reference to genomic applications. Thecontributors, who are among the most prominent researchers on the theory ofstatistics for high dimensional inference, present new theories and methods, aswell as challenging applications and computational solutions. Specific themesinclude, among others, variable selection and screening, penalised regressionsparsity, thresholding, low dimensional structures, computational challengesnon-convex situations, learning graphical models, sparse covariance andprecision matrices, semi- and non-parametric formulations, multiple testingclassification, factor models, clustering, and preselection.Highlighting cutting-edge researchand casting light on future research directions, the contributions will benefitgraduate students and researchers in computational biology, statistics and themachine learning community.…