VC Dimension of Neural Networks

@inproceedings{Sontag1998VCDO,
  title={VC Dimension of Neural Networks},
  author={Eduardo D. Sontag},
  year={1998}
}
This paper presents a brief introduction to Vapnik-Chervonenkis (VC) dimension, a quantity which characterizes the difficulty of distribution-independent learning. The paper establishes various elementary results, and discusses how to estimate the VC dimension in several examples of interest in neural network theory. 
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