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Toast119 t1_jb16zt9 wrote

Reply to comment by Chadssuck222 in [R] [N] Dropout Reduces Underfitting - Liu et al. by radi-cho

I think it's because Dropout is usually seen as a method for reducing overfitting and this paper is claiming and supporting that it is also useful for reducing underfittting as well.

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farmingvillein t1_jb18evq wrote

Yes. In the first two lines of the abstract:

> Introduced by Hinton et al. in 2012, dropout has stood the test of time as a regularizer for preventing overfitting in neural networks. In this study, we demonstrate that dropout can also mitigate underfitting when used at the start of training.

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