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Estimation and Testing Under Sparsity École d'Été de Probabilités de Saint-Flour XLV - 2015 /
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 v...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
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| Formato: | Electrónico eBook |
| Idioma: | Inglés |
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Cham :
Springer International Publishing : Imprint: Springer,
2016.
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| Edición: | 1st ed. 2016. |
| Colección: | École d'Été de Probabilités de Saint-Flour ;
2159 |
| Temas: | |
| Acceso en línea: | Texto Completo |
| Sumario: | 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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| Descripción Física: | XIII, 274 p. online resource. |
| ISBN: | 9783319327747 |