Robust Statistics: Theory and Methods (Wiley Series in Probability and Statistics) (Hardcover) Preface. 1. Introduction. 1.1 Classical and robust approaches to statistics. 1.2 Mean and standard deviation. 1.3 The “three-sigma edit” rule. 1.4 Linear

Contents 1 Introduction 1 1.1 Majorization Theory 1 1.2 Matrix-Monotone Functions 3 1.3 Classification and Organization 4 1.4 Notation 7 2 Majorization Theory 9 2.1 Definition and Examples 10 2.2 Basic Results 18 2.3 Majorization and Optimization 30

1 Introduction 1 1.1 Classical and robust approaches to statistics 1 1.2 Mean and standard deviation 2 1.3 The “three-sigma edit” rule 5 1.4 Linear regression 7 1.4.1 Straight-line regression 7 1.4.2 Multiple linear regression 9 1.5 Correlation coef

在不久的将来，深度学习将会取得更多的成功，因为它需要很少的手工工程，它可以很容易受益于可用计算能力和数据量的增加。目前正在为深度神经网络开发的新的学习算法和架构只会加速这一进程。Probability: Foundations A probability space(Q2, F, P)consists of a set S2 of"possible outcomes a set of events. which are subsets of n2 a probability measure P: