Statistical learning by sparse deep neural networks

Felix Abramovich
11/15/2023
math.STcs.LGstat.ME

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Abstract

We consider a deep neural network estimator based on empirical risk minimization with l_1-regularization. We derive a general bound for its excess risk in regression and classification (including multiclass), and prove that it is adaptively nearly-minimax (up to log-factors) simultaneously across the entire range of various function classes.

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Cite this paper

@article{abramovich2023statistical,
  title  = {Statistical learning by sparse deep neural networks},
  author = {Felix Abramovich},
  year   = {2023},
  eprint = {2311.08845},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2311.08845v1}
}

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