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by hillbig on 2018-07-02 (UTC).

While DropOut has been considered to prevent the co-adaption among hidden neurons to regularize the model, DropOut actually makes gradient flows even when the activation functions are saturated and helps the optimization converges to the flat minima. https://t.co/YEH33wWqRZ

— Daisuke Okanohara (@hillbig) July 2, 2018
research
by dennybritz on 2018-07-02 (UTC).

Dropout has been a standard technique for years, but we’re still finding new ways to interpret it.

I tend to think of new techniques/architectures as an advancement in either regularization or optimization/gradient flow, but sometimes it’s difficult to tell which one it is. https://t.co/74lt0VtExG

— Denny Britz (@dennybritz) July 2, 2018
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