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stat.ML2026
Approximation of Analytic Functions by ReLU Neural Networks with Adjustable Depth and Width
Yanming Lai, Defeng Sun, Yang Wang
In contrast to most studies on neural network approximation theory that characterize results through a single parameter, such as the total number of network parameters, \cite{shen2…
stat.ML2025
Approximation Bounds for Transformer Networks with Application to Regression
Yuling Jiao, Yanming Lai, Defeng Sun +2
We explore the approximation capabilities of Transformer networks for Hölder and Sobolev functions, and apply these results to address nonparametric regression estimation with depe…