9 citations · 10 across the 2 of their papers we have counts for
5 papers · 1 filter
Approximation Rates for Shallow ReLU Neural Networks on Sobolev Spaces via the Radon Transform
Tong Mao, Jonathan W. Siegel, Jinchao Xu
Let be a bounded domain. We consider the problem of how efficiently shallow neural networks with the ReLU activation function can approximate functions…
Weighted variation spaces and approximation by shallow ReLU networks
Ronald DeVore, Robert D. Nowak, Rahul Parhi +1
We investigate the approximation of functions on a bounded domain by the outputs of single-hidden-layer ReLU neural networks of width . This form of…
Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural Networks
Jonathan W. Siegel
We study the following two related problems. The first is to determine to what error an arbitrary zonoid in can be approximated in the Hausdorff distance by a su…
Sharp Convergence Rates for Matching Pursuit
Jason M. Klusowski, Jonathan W. Siegel
We study the fundamental limits of matching pursuit, or the pure greedy algorithm, for approximating a target function by a linear combination of elements from a di…
Sharp Lower Bounds on the Approximation Rate of Shallow Neural Networks
Jonathan W. Siegel, Jinchao Xu
We consider the approximation rates of shallow neural networks with respect to the variation norm. Upper bounds on these rates have been established for sigmoidal and ReLU activati…