Explicit integral representations and quantitative bounds for two-layer ReLU networks
stat.ML updates on arXiv.org
Anthony Lee
arXiv:2604.23260v1 Announce Type: new Abstract: An approach to construct explicit integral representations for two-layer ReLU networks is presented, which provides relatively simple representations for any multivariate polynomial. Quantitative bounds are provided for a particular, sharpened ReLU integral representation, which involves a harmonic extension and a projection. The bounds demonstrate that functions can be approximated with $L^{2}(\mathcal{D})$ errors that do not depend explicitly on dimension or degree, but rather the coefficients of their monomial expansions and the distribution $\mathcal{D}$.
