• DOI:10.1007/s10994-020-05929-w
Corpus ID: 4811672

Regularisation of Neural Networks by Enforcing Lipschitz Continuity

@article{Gouk2018RegularisationON,
  title={Regularisation of Neural Networks by Enforcing Lipschitz Continuity},
  author={Henry Gouk and Eibe Frank and B. Pfahringer and M. Cree},
  journal={ArXiv},
  year={2018},
  volume={abs/1804.04368}
}

Henry Gouk, Eibe Frank, +1 author M. Cree

Published 2018

Computer Science, Mathematics

ArXiv

We investigate the effect of explicitly enforcing the Lipschitz continuity of neural networks with respect to their inputs. To this end, we provide a simple technique for computing an upper bound to the Lipschitz constant of a feed forward neural network composed of commonly used layer types and demonstrate inaccuracies in previous work on this topic. Our technique is then used to formulate training a neural network with a bounded Lipschitz constant as a constrained optimisation problem that… CONTINUE READING

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