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arXiv · 2108.04052

Training of deep residual networks with stochastic MG/OPT

Cyrill von Planta·Alena Kopanicakova·Rolf Krause
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Abstract

We train deep residual networks with a stochastic variant of the nonlinear multigrid method MG/OPT. To build the multilevel hierarchy, we use the dynamical systems viewpoint specific to residual networks. We report significant speed-ups and additional robustness for training MNIST on deep residual networks. Our numerical experiments also indicate that multilevel training can be used as a pruning technique, as many of the auxiliary networks have accuracies comparable to the original network.

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Cyrill von Planta, Alena Kopanicakova, Rolf Krause. 2021-08-09. Training of deep residual networks with stochastic MG/OPT. https://arxiv.org/abs/2108.04052

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