목록graph deep learning/#2 Basics of Math and Graph (2)
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2.2.1 Basic Concepts and Formulas Random variable a variable that has a random value. X로부터 $x_1$와 $x_2$의 두 변수가 나올 수 있게 될 경우 아래의 식이 성립한다. $$P(X=x_1) + P(X=x_2)=1$$] Joint probability 두 개의 random variable X, Y에서 각각 $x_1$와 $y_1$가 뽑힐 확률 $P(X=x_1, Y=y_1)$ Conditional Probability $Y=y_1$가 뽑혔을 때 $X=x_1$가 같이 뽑힐 확률 $P(X=x_1|Y=y_1)$ fundamental rules sum rule: $P(X=x)=\sum_y P(X=x, Y=y)$ product rule: $P(..
2.1.1 Basic Concepts Scalar: A number Vector: A column of ordered numbers $$ x=\begin{bmatrix} x_1 \\ x_2 \\ \vdots \\x_n \end{bmatrix}$$ norm of vector: the length $L_p$ norm: $||x||_p = (\sum_{i=1}^{n}|x_i|^p)^{1/p}$ $L_1$ norm: $||x||_1 = (\sum_{i=1}^{n}|x_i|)$ $L_2$ norm: $||x||_2 = \sqrt{\sum_{i=1}^{n}{x_i}^2}$ --> used to measure the length of vectors $L_\infty$ norm: $||x||_\infty = max_i..