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[D] Relationship Between Neural Networks and Universal Approximation Theorem
For this theorem to work, i.e. for the function fϵfϵ to approximate the function ff at some arbitrary level of precision - this theorem seems to specifically require that the function σσ to not be a polynomial.
In a certain sense, it seems like being polynomial here has a negative connotation, in the sense that it might prevent the results of this theorem from being true.
Regarding this, I had the following questions:
Could this theorem have been written …!-->