4min chapter

Machine Learning Street Talk (MLST) cover image

#96 Prof. PEDRO DOMINGOS - There are no infinities, utility functions, neurosymbolic

Machine Learning Street Talk (MLST)

CHAPTER

Is There a Clip With NTK Isn't There Like a Closed Form Solution?

Mark O'Mara: I remember you did the paper and that that introduced elements of NTK theory as well, which might be an argument against the discreteness of the optimization. But also I wanted to trade off the two types of ways that are going against the discrete. So let's say there was a close form solution and it was like an infinite kernel when it represented some neural network doesn't that right? And now the new tangent kernel does not assume that your network is infinite. Most of the three that people have done with it assumes that the network is infinitely wide, but might, but the definition absolutely does not require that. It's for any architecture that you use

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