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Lecture 1 Introduction

1) 15:20 least squares is easier to solve than least absolute deviations, because it is smooth while the other is not

2) 28:00

第一部分是确定的像素，第二部分total variation.

3) 1:04:22

Lecture 2 Convexity I: Sets and functions

1) 26:20 norm cone: 对于内部点, norm cone为0向量, 对于边界点, norm cone 就是法向量相夹的cone, 如果只有一个法向量, 则该法向量为norm cone.

2) 46:46

Operations preserving convexity: Scaling and translation中a为标量 Affine images and preimages中 A <script type="math/tex" id="MathJax-Element-1">A</script>为矩阵

3) 1:01:25

Lecture 3 Convexity II: Optimization basics

1) 6:23

2) 30:05