Spectral Convergence of Random Feature Method in Multiple Dimensions
- URL: http://arxiv.org/abs/2609.03401v1
- Date: Thu, 03 Sep 2026 06:01:00 GMT
- Title: Spectral Convergence of Random Feature Method in Multiple Dimensions
- Abstract summary: We first prove spectral convergence of the random feature method (RFM) for multidimensional targets in Sobolev, Gevrey, ultra-analytic, and bandlimited classes.<n>The analysis identifies a common mechanism: the same spectral approximation that yields high accuracy also drives severe ill-conditioning.
- Score: 5.361030050051251
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We first prove spectral convergence of the random feature method (RFM) for multidimensional targets in Sobolev, Gevrey, ultra-analytic, and bandlimited classes. The analysis establishes general high-probability approximation estimates in the interpolation scale generated by a kernel integral operator. On a single event determined only by the sampled features, one random space approximates every target in a prescribed source ball; moreover, for each target, a single coefficient vector defines an approximant that attains spectral accuracy simultaneously in all admissible error norms. For both regularity-adapted frequency distributions and uniform distributions on growing frequency windows, the resulting rates range from super-exponential to algebraic, depending on the regularity of the target. Second, we establish abstract error estimates for strong- and weak-form RFM discretizations, thereby converting the preceding approximation bounds into convergence estimates for multidimensional second-order elliptic boundary value and eigenvalue problems. Finally, for random feature matrices (RFMtxs), we prove super-exponential singular-value decay with Fourier features and exponential decay with $\tanh$ features, together with corresponding condition-number lower bounds. The analysis identifies a common mechanism: the same spectral approximation that yields high accuracy also drives severe ill-conditioning.
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