90折
High-dimensional Statistics ― A Non-asymptotic Viewpoint
- 系列名：Cambridge Series in Statistical and Probabilistic
- ISBN13：9781108498029
- 出版社：Cambridge Univ Pr
- 作者：Martin J. Wainwright
- 裝訂／頁數：精裝／568頁
- 規格：26cm*18.4cm*3.8cm (高/寬/厚)
- 出版日：2019/04/30
定 價：NT$ 3899 元
優惠價：90 折 3509 元
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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.
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