High-Dimensional Statistics

High-Dimensional Statistics

A Non-Asymptotic Viewpoint

Wainwright, Martin J.

Cambridge University Press

02/2019

568

Dura

Inglês

9781108498029

15 a 20 dias

1200

Descrição não disponível.
1. Introduction; 2. Basic tail and concentration bounds; 3. Concentration of measure; 4. Uniform laws of large numbers; 5. Metric entropy and its uses; 6. Random matrices and covariance estimation; 7. Sparse linear models in high dimensions; 8. Principal component analysis in high dimensions; 9. Decomposability and restricted strong convexity; 10. Matrix estimation with rank constraints; 11. Graphical models for high-dimensional data; 12. Reproducing kernel Hilbert spaces; 13. Nonparametric least squares; 14. Localization and uniform laws; 15. Minimax lower bounds; References; Author index; Subject index.