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I am reading a recent paper "Generalization in Deep Learning" and I am unable to understand a step. In this step, they first take neural network as a direct acyclic graph(DAG) and described output of neural network as follows,

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and then they decomposed generalization gap as follows,

enter image description here

without any explanation. Here z is,

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Can someone explain this or point me towards the right direction.

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