Learning between the peaks: sharp asymptotics for kernel ridge regression under power-law anisotropy

arXiv:2608. 28564v1 Announce Type: cross Abstract: We study kernel ridge regression under anisotropic Gaussian data, where the input covariance decays as a power law with exponent $\alpha\geq 0$ for polynomial inner-product kernels.

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