Machine Learning & AI

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Dropout (Inverted)

Randomly zeroes activations during training to prevent co-adaptation.

Formula

\tilde{x} = \dfrac{x\odot m}{1-p}

Variables

mRandom 0/1 mask

pDrop probability

\odotElement-wise product

Example

p=0.5 drops half the units each step

Did You Know?

Dropout mimics training an ensemble of many thinner networks that share weights.

deep learning regularization

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