the paper be accepted
–Neural Information Processing Systems
Regarding our proof techniques, the proof in Thm. 1 for NTK with two layers and bias borrows techniques from [6]. Our proof technique for deep networks uses the algebra of RKHSs and is therefore novel in this context. Thm. 2 derives bounds that result from the relation between the Fourier expansion of the Laplace kernel in NTK (established in Thm. 4) and identifying the spaces fixed under the appropriate integral transform. "why they need additional parameters a, b, c." We note that analogously NTK becomes sharper for deeper networks.
Neural Information Processing Systems
Oct-2-2025, 02:00:42 GMT
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