普林斯顿算法 普林斯顿算法Cousera课程作业

Linear Systems Theory(by Princeton University Press)，another reference to Linear System Theory and Design (3rd ed)

OASIS, Open Annotations of Single Image Surfaces, a dataset for single-image 3D in the wild consisting of detailed 3D geometry for 140,000 images by Princeton University. OASIS开放单个物体表面图像数据集由普林斯顿大学出品， 含有140000张单个物体的详细3D图片。 OASIS paper.pdf

英文原版，普林斯顿的算法教材，经典之作。基于C++

The Princeton Companion to Applied Mathematicsdescribes what applied mathematics is about, why it is important, its connections with other disciplines, and some of the main areas of current research. It also explains what applied mathematicians do, which includes not only studying the subject itself but also writing about mathematics, teaching it, and influencing policy makers.

普林斯顿数学指南 PDF

written by Aharon Ben-Tal Laurent El Ghaoui Arkadi Nemirovski Copyright © 2009 by Princeton University Press PART I. ROBUST LINEAR OPTIMIZATION 1 Chapter 1. Uncertain Linear Optimization Problems and their Robust Counterparts 3 1.1 Data Uncertainty in Linear Optimization 3 1.2 Uncertain Linear Problems and their Robust Counterparts 7 1.3 Tractability of Robust Counterparts 16 1.4 Non-Affine Perturbations 23 1.5 Exercises 25 1.6 Notes and Remarks 25 Chapter 2. Robust Counterpart Approximations of Scalar Chance Constraints 27 2.1 How to Specify an Uncertainty Set 27 2.2 Chance Constraints and their Safe Tractable Approximations 28 2.3 Safe Tractable Approximations of Scalar Chance Constraints: Basic Examples 31 2.4 Extensions 44 2.5 Exercises 60 2.6 Notes and Remarks 64 Chapter 3. Globalized Robust Counterparts of Uncertain LO Problems 67 3.1 Globalized Robust Counterpart — Motivation and Definition 67 3.2 Computational Tractability of GRC 69 3.3 Example: Synthesis of Antenna Arrays 70 3.4 Exercises 79 3.5 Notes and Remarks 79 Chapter 4. More on Safe Tractable Approximations of Scalar Chance Constraints 81 4.1 Robust Counterpart Representation of a Safe Convex Approximation to a Scalar Chance Constraint 81 4.2 Bernstein Approximation of a Chance Constraint 83 4.3 From Bernstein Approximation to Conditional Value at Risk and Back 90 4.4 Majorization 105 4.5 Beyond the Case of Independent Linear Perturbations 109 4.6 Exercises 136 4.7 Notes and Remarks 145 PART II. ROBUST CONIC OPTIMIZATION 147 Chapter 5. Uncertain Conic Optimization: The Concepts 149 5.1 Uncertain Conic Optimization: Preliminaries 149 5.2 Robust Counterpart of Uncertain Conic Problem: Tractability 151 5.3 Safe Tractable Approximations of RCs of Uncertain Conic Inequalities 153 5.4 Exercises 156 5.5 Notes and Remarks 157 Chapter 6. Uncertain Conic Quadratic Problems with Tractable RCs 159 6.1 A Generic Solvable Case: Scenario Uncertainty 159 6.2 Solvable Case I: Simple Interval Uncertainty 160 6.3 Solv

E.M.Stein编写的Princeton大学数学系本科教程 四部曲之一

Princeton Edu -- HotspotOverview.pdf

The Princeton Companion to Applied Mathematics