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Neural Tangent Kernel

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If you have a question about this talk, please contact Robert Pinsler.

There has recently been a large amount of interest on the Neural Tangent Kernel (NTK), because of its applicability to the theory of deep learning. The NTK allows for a description of the training dynamics of wide neural networks, by describing the evolution of the network in function space. The talk will discuss some of the research on the following questions: (1) what is the NTK , (2) what is it good for, (3) when does it predict the training behaviour of the network, and (4) what can’t it do?

This talk is part of the Machine Learning Reading Group @ CUED series.

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