Meaning of the following notation of Expected value.

Question

While going through the slides of my course on Machine Learning, I came to the following notation:

$$E_{(x,y)\sim P}(y-\hat{\omega}_0-\hat\omega_1x)^2$$

What does this notation mean? So far I have only come across notation like $$E_{f(x)} g(x).$$ This notation is completely new to me. Can somebody please explain me this?

Answer 1

This probably means that the joint distribution of $(x, y)$ is $P$ and the expected value is taken with respect to $(x, y)$.