Statistics for High-Dimensional Data

1. Introduction
Peter Bühlmann, Sara Geer

2. Lasso for linear models
Peter Bühlmann, Sara Geer

3. Generalized linear models and the Lasso
Peter Bühlmann, Sara Geer

4. The group Lasso
Peter Bühlmann, Sara Geer

5. Additive models and many smooth univariate functions
Peter Bühlmann, Sara Geer

6. Theory for the Lasso
Peter Bühlmann, Sara Geer

7. Variable selection with the Lasso
Peter Bühlmann, Sara Geer

8. Theory for ℓ1/ℓ2-penalty procedures
Peter Bühlmann, Sara Geer

9. Non-convex loss functions and ℓ1-regularization
Peter Bühlmann, Sara Geer

10. Stable solutions
Peter Bühlmann, Sara Geer

11. P-values for linear models and beyond
Peter Bühlmann, Sara Geer

12. Boosting and greedy algorithms
Peter Bühlmann, Sara Geer

13. Graphical modeling
Peter Bühlmann, Sara Geer

14. Probability and moment inequalities
Peter Bühlmann, Sara Geer

Keywords: Statistics, Statistical Theory and Methods, Probability and Statistics in Computer Science