Estimation and Testing Under Sparsity : École d'Été de Probabilités de Saint-Flour XLV – 2015
SpringerSivumäärä: 274 sivuaAsu: Pehmeäkantinen kirjaJulkaisuvuosi: 2016, 29.06.2016 (lisätietoa)Kieli: Englanti 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.
Tilaustuote | Arvioimme, että tuote lähetetään meiltä noin 17-20 arkipäivässä