On the Implicit Bias of Dropout


Poorya Mianjy, Raman Arora, Rene Vidal ;
Proceedings of the 35th International Conference on Machine Learning, PMLR 80:3540-3548, 2018.


Algorithmic approaches endow deep learning systems with implicit bias that helps them generalize even in over-parametrized settings. In this paper, we focus on understanding such a bias induced in learning through dropout, a popular technique to avoid overfitting in deep learning. For single hidden-layer linear neural networks, we show that dropout tends to make the norm of incoming/outgoing weight vectors of all the hidden nodes equal. In addition, we provide a complete characterization of the optimization landscape induced by dropout.

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