RM+ML: 19. General Remarks on Random Feature Model

The lecture notes for the course can be found at https://rolandspeicher.com/wp-content...
neural network, random features, non-linear random matrix theory

0:00 Introducing non-linearities
4:18 Random features
6:50 Non-linear random matrix theory
7:50 Product of two Wishart matrices
12:29 Dealing with non-linearity


The goal of this lecture series is to cover mathematical interesting aspects of neural networks, in particular, those related to random matrices. In this 19th lecture we make the transition from linear regression to the random feature model, by adding one hidden layer and non-linearities. This poses new problems on random matrices which will be addressed in the next videos.