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math.PR2023
A Quantitative Functional Central Limit Theorem for Shallow Neural Networks
Valentina Cammarota, Domenico Marinucci, Michele Salvi +1
We prove a Quantitative Functional Central Limit Theorem for one-hidden-layer neural networks with generic activation function. The rates of convergence that we establish depend he…
stat.ML2023
How many samples are needed to leverage smoothness?
Vivien Cabannes, Stefano Vigogna
A core principle in statistical learning is that smoothness of target functions allows to break the curse of dimensionality. However, learning a smooth function seems to require en…