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Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS

Machine Learning 2021-03-19 v5 Statistics Theory Machine Learning Statistics Theory

Abstract

We prove that the reproducing kernel Hilbert spaces (RKHS) of a deep neural tangent kernel and the Laplace kernel include the same set of functions, when both kernels are restricted to the sphere Sd1\mathbb{S}^{d-1}. Additionally, we prove that the exponential power kernel with a smaller power (making the kernel less smooth) leads to a larger RKHS, when it is restricted to the sphere Sd1\mathbb{S}^{d-1} and when it is defined on the entire Rd\mathbb{R}^d.

Cite

@article{arxiv.2009.10683,
  title  = {Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS},
  author = {Lin Chen and Sheng Xu},
  journal= {arXiv preprint arXiv:2009.10683},
  year   = {2021}
}

Comments

Accepted to ICLR 2021

R2 v1 2026-06-23T18:43:31.615Z