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Estimation and Testing Under Sparsity: Ecole D'ete De Probabilites De Saint-flour Xlv - 2015
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Summaries and Reviews
Amazon.com description: Product Description: Taking the Lasso method as its starting point, this book describes the main ingredients needed to study general loss functions and sparsity-inducing regularizers. It also provides a semi-parametric approach to establishing confidence intervals and tests. Sparsity-inducing methods have proven to be very useful in the analysis of high-dimensional data. Examples include the Lasso and group Lasso methods, and the least squares method with other norm-penalties, such as the nuclear norm. The illustrations provided include generalized linear models, density estimation, matrix completion and sparse principal components. Each chapter ends with a problem section. The book can be used as a textbook for a graduate or PhD course.

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Paperback
Book cover for 9783319327730
 
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from Springer Verlag (June 24, 2016)
9783319327730 | details & prices | List price $59.99
About: Taking the Lasso method as its starting point, this book describes the main ingredients needed to study general loss functions and sparsity-inducing regularizers.

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