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RMML 20 Asymptotic Eigenvalue Distribution in the Random Feature Model
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=Es59qcUoryo
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 Recap of random feature model • 7:50 Theorem on asymptotic eigenvalue distribution • 23:22 Special cases of theorem • 34:15 General form of the result • The goal of this lecture series is to cover mathematical interesting aspects of neural networks, in particular, those related to random matrices. In this 20th lecture we state the theorem on the asymptotic eigenvalue distribution in the random feature model, look on some special cases and point out that the effect of the non-linearity is to add an independent noise to the linear model.
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