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Author

Jia Li

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Preprint Aug 2026

Sharp Sobolev Approximation on General Domains by Linearized Shallow Networks with Analytic Activations

It is proved that quasi-Chebyshev parameter sets with univariate resolution $m$ generate fixed feature spaces attaining the sharp $H^r$-to-to-H^s$ approximation order for a class of analytic activations satisfying a quantitative non-cancellation condition on their Taylor coefficients.

Jia Li, Tong Mao, Jin-Chao Xu · 2 citations

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