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Estimation and Testing Under Sparsity: École D'été de Probabilités de Saint-Flour xlv – 2015 (Lecture Notes in Mathematics) (in English)
Sara Van De Geer (Author)
·
Springer
· Paperback
Estimation and Testing Under Sparsity: École D'été de Probabilités de Saint-Flour xlv – 2015 (Lecture Notes in Mathematics) (in English) - Sara Van De Geer
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Synopsis "Estimation and Testing Under Sparsity: École D'été de Probabilités de Saint-Flour xlv – 2015 (Lecture Notes in Mathematics) (in English)"
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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The book is written in English.
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