Author

Yun-Fei Yang

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#machine learning Preprint Sep 2026

Minimax rates for learning spectral Barron functions by deep ReLU neural networks

We study how well deep neural networks approximate and learn spectral Barron functions. Recent studies have shown that these function classes can be efficiently approximated by shallow neural networks without suffering from the curse of dimensionality. We complement these results by providing new approximation bounds f...

Song-Qiu Ma, Yun-Fei Yang · 0 citations

#machine learning Preprint Sep 2026

Error bounds in Sobolev norms for approximations with norm constrained ReLU neural networks

This work analyzes how well Sobolev functions in W^{n,p} can be approximated by neural networks with width $W$, depth $L$ and path norm bounded by $K$ when the approximation error is measured in the $W^{1,p}$-norm.

Xian-Jun Li, Yun-Fei Yang · 0 citations