Этот веб-сайт требует, чтобы для Вашего браузера был включен JavaScript.
Пожалуйста, включите JavaScript и перезагрузите страницу.
Для веб-сайта требуется, чтобы Ваш браузер разрешил использование файлов cookie для входа в систему.
Пожалуйста, активируйте cookies и перезагрузите страницу.
Carte romana
Carte rusa
Carte engleza
Vezi toate cartile
Top branduri cosmetica
Cosmetica Coreeana
Machiaj
Ingrijire ten
Ingrijire par
Ingrijire corp
Produse de baie
Igiena orala
Igiena intima
Igiena sexuala
Cosmetice barbati
Seturi cadou
Naturale si organice
Vezi toate cosmeticele
Top branduri dermatocosmetica
Protectie solara
Seturi cadou si pachete promo
Parfumuri pentru femei
Top branduri femei
Premium brands femei
Parfumuri unisex
Vezi toate parfumurile
Parfumuri pentru barbati
Top branduri barbati
Premium brands barbati
Jucarii si jocuri
Hrana si articole copii
Scutece si servetele
Rechizite si papetarie
Vezi toate produsele
Nutritie & Suplimente
Branduri
Certificate Cadou
Felicitari
Plicuri
Cutii si Accesorii
Martin J. WainwrightHigh-Dimensional Statistics, Hardcover
в Пункте приема от 99,9 лей
Даже распечатанный
Перед оплатой
Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level. It includes chapters that are focused on core methodology and theory - including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices - as well as chapters devoted to in-depth exploration of particular model classes - including sparse linear models, matrix models with rank constraints, graphical models, and various types of non-parametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and adapt modern statistical methods suited to large-scale data.
Мы хотели бы узнать Ваше мнение! Оценить и пересмотреть этот пункт
Нет ни одного отзыва от других пользователей.