Algorithmic High-Dimensional Robust Statistics

Algorithmic High-Dimensional Robust Statistics This reference text offers a clear unified treatment for graduate students, academic researchers, and professionals interested in understanding and developing statistical procedures for high-dimensional data that are robust to idealized modeling assumptions, including robustness to model misspecification and to adversarial outliers in the dataset. Autor: Ilias (University of Wisconsin-Madison) Diakonikolas, Daniel M. (University of California Kane Wydawnictwo: Cambridge University Press Rok wydania: 2023 Okładka: twarda Liczba stron: 300 Wymiary: 16 x 23.7 x 2.4 cm Ilustracje: Worked examples or Exercises Język: angielski ISBN: 9781108837811