# A Principle of Least Action for the Training of Neural Networks

@article{Karkar2020APO, title={A Principle of Least Action for the Training of Neural Networks}, author={Skander Karkar and Ibrahhim Ayed and Emmanuel de B'ezenac and Patrick Gallinari}, journal={ArXiv}, year={2020}, volume={abs/2009.08372} }

Neural networks have been achieving high generalization performance on many tasks despite being highly over-parameterized. Since classical statistical learning theory struggles to explain this behavior, much effort has recently been focused on uncovering the mechanisms behind it, in the hope of developing a more adequate theoretical framework and having a better control over the trained models. In this work, we adopt an alternate perspective, viewing the neural network as a dynamical system…

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