FreezeOut: Accelerate Training by Progressively Freezing Layers

15 Jun 2017Andrew BrockTheodore LimJ. M. RitchieNick Weston

The early layers of a deep neural net have the fewest parameters, but take up the most computation. In this extended abstract, we propose to only train the hidden layers for a set portion of the training run, freezing them out one-by-one and excluding them from the backward pass... (read more)

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